DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQe2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and /n re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
a. A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321 (d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
b. Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with
37 CFR 3.73(b).
Claims 1-20 are rejected on the ground of nonstatutory obviousness type double patenting as being unpatentable over claims 1-20 of U.S. Patent Application No. 18/397025.
As can be seen from the table below (underlined elements), Claim 1 of U.S. Patent Application No. 18/397025 show all the limitations of claim 1 of the instant application except detect a dye mixing ratio that matches an absorbance graph of a buyer order, on the basis of an artificial intelligence model..
Claim 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of copending Application No. 18397025 in view of Yu et al. (US20170131147), hereinafter referred to as ‘Yu’.
This is a provisional nonstatutory double patenting rejection.
Yu discloses store in the storage unit into absorbance data and detecting a dye mixing ratio that matches an absorbance graph of a buyer order, on the basis of an artificial intelligence model (Alternatively, the computer program product may reside in a non-transitory computer-readable medium such as a server system remote from the computing device but communicatively linked to the computing device such that execution of the computer program product directs the performance of a color sensing, storage and comparison method according to the present disclosure, at least part of which includes steps for generating a user interface on a display [0037];In one embodiment, the entire supervised training set of raw scans and reference scans may be stored in a database. When an unadjusted color reading needs to be aligned, a machine learning technique may be used (for example, a K Nearest Neighbor, Artificial Neural Network, or other machine learning technique may be used) [0055]).
With regards to Claim 1, it would be obvious to one of ordinary skill in the art to modify a current separation method as claimed in Claim 1 of U.S. Patent No. 18397025, in view of Yu, to obtain a weighted average of the reference scans and obtain results that are extremely accurate for colors in or near the designated color set. ensure precise control, prevent equipment damage, and maintain system safety and efficiency.
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Claims of US Patent Application No.
#18397025
Instant Claims
1
An apparatus for predicting an absorbance spectrum of a mixed dye based on CCM reflectance data, comprising: an input module receiving input of a customer order for dyeing; and a processor reproducing an absorbance spectrum through conversion of reflectance data in a QTX file of the customer order, wherein the processor generates absorbance spectra and predicted colors through conversion of reflectance data of single-color dyes in a dyeing factory; implements a predicted absorbance spectrum of a mixed dye produced according to a recommended single-color dye mixing ratio corresponding to CCM values of the customer order; compares the predicted absorbance spectrum of the mixed dye with the absorbance spectrum according to the customer order; and complements or corrects the recommended single-color dye mixing ratio to match the predicted absorbance spectrum of the mixed dye to the absorbance spectrum according to the customer order.
1
An apparatus for detecting a dye mixing ratio, comprising: a storage unit configuration to store computer color matching (CCM) colorimetric data for each dye concentration; and a processor configuration to convert the CCM colorimetric data for each dye concentration store in the storage unit into absorbance data and detect a dye mixing ratio that matches an absorbance graph of a buyer order, on the basis of an artificial intelligence model.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 1 rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, as based on a disclosure which is not enabling. The disclosure does not enable one of ordinary skill in the art to practice the invention with regards to converting the CCM colorimetric data for each dye concentration store in the storage unit into absorbance data, which is critical or essential to the practice of the invention but not included in the claim(s). See In re Mayhew, 527 F.2d 1229, 188 USPQ 356 (CCPA 1976).
Claim 1 states that “a processor configuration to convert the CCM colorimetric data for each dye concentration store in the storage unit into absorbance data” which omits an essential limitation/step related to converting the CCM colorimetric data for each dye concentration store in the storage unit into absorbance data, as discussed in the specification in paragraph page 5 lines 6-9.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. —The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2 and 12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 2 and 12 contains the trademark/trade name QTX. Where a trademark or trade name is used in a claim as a limitation to identify or describe a particular material or product, the claim does not comply with the requirements of 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph. See Ex parte Simpson, 218 USPQ 1020 (Bd. App. 1982). The claim scope is uncertain since the trademark or trade name cannot be used properly to identify any particular material or product. A trademark or trade name is used to identify a source of goods, and not the goods themselves. Thus, a trademark or trade name does not identify or describe the goods associated with the trademark or trade name. In the present case, the trademark/trade name is used to identify/describe a reflectance for each dye concentration and, accordingly, the identification/description is indefinite.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 6-8, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Osumi et al. (US6362885), hereinafter referred to as ‘Osumi’ and in further view of Nam et al. (KR102521983), hereinafter referred to as ‘Nam’.
Regarding Claim 1, Osumi discloses an apparatus for detecting a dye mixing ratio, comprising: a storage unit configuration to store computer color matching (CCM) colorimetric data for each dye concentration (The method of the present invention is further characterized in that, while determining the formulating ratio of the metallic or pearlescent pigment to the colorant or the formulating amount of the metallic or pearlescent pigment in the computer color matching of the coating composition, i.e. dye concentration, containing the metallic or pearlescent pigment, the predictive reproduction gonio-gonio-spectral reflectances is subjected to correction procedure comprising the steps of i) generating the gonio-spectral reflectance data of a coating comprising one or more metallic or pearlescent pigments or one or more metallic or pearlescent pigments and one or more colorants inclusive of a translucent pigment and the formulating amount or ratio data thereof or said two kinds of data and coating thickness data for taking into account the influence of under coating color or substrate color and coating thickness as measured for one or a plurality of coated plate samples, ii) storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching , Col. 4, Lines 5-27); and a processor configuration to convert the CCM colorimetric data for each dye concentration store in the storage unit into absorbance data (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27) and detect a dye mixing ratio that matches an absorbance graph of a buyer order, on the basis of an artificial intelligence model (In view of the above state of the art, the object of the present invention is to provide a method for computer-aided color matching that easily and accurately computes a formulating ratio of colorants to metallic or pearlescent pigments with the desired hue and luster characteristics of a metallic or pearlescent coating composition, i.e. buyer order, Col. 3, Lines 43-48).
However, Osumi does not explicitly disclose detect a dye mixing ratio that matches an absorbance graph of a buyer order, on the basis of an artificial intelligence model.
Nevertheless, Nam discloses detect a dye mixing ratio on the basis of an artificial intelligence model (The generating device (100) can automatically instruct the equipment to optimal operating conditions and optimal mixing ratios. To this end, the generating device (100) may be equipped with a generating model generated through machine learning [0037]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Regarding Claim 3, Osumi and Nam disclose the claimed invention discussed in claim 1.
Osumi discloses the processor converts a reflectance under buyer-order light source conditions into an absorbance (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27) and calculates a slope for each wavelength section of the absorbance data to use the calculated slope as rising and falling trend information of the absorbance graph (…storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic, i.e. calculates a slope for each wavelength, (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching, Col. 4, Lines 19-26), and calculates an absorbance area in a specific absorbance wavelength section to use the calculated area as information on a color intensity (…storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching, Col. 4, Lines 19-26; …the incident energy of viewing light at wavelength .lambda. I.sub.o (.theta., .lambda.): the energy of light received at viewing angle .theta. and wavelength .lambda. C.sub.ori (.theta., .lambda.) the scattering orientation function of light provided by metallic or pearlescent pigment T.sub.trap (.lambda., x): the efficiency of trapping of viewing light at metallic or pearlescent pigment concentration, Col. 13, Lines 1-8).
Regarding Claim 6, Osumi and Nam disclose the claimed invention discussed in claim 1.
Osumi discloses the processor constructs a training dataset (…a fuzzy deduction algorithm which, using gonio-spectral reflectance data of coated samples prepared in optional formulations using a plurality of colorants and a plurality of metallic or pearlescent pigments, sample formulation data, and sample coating condition data as stored in a memory of a computer ahead of time, Col. 8, Lines 11-17), and applies a test dataset to the artificial intelligence model to detect the dye mixing ratio (Developed to accomplish the above object, the present invention is a method of determining a formulating ratio of a colorant to a metallic or pearlescent pigment or a formulating amount of a metallic or pearlescent, Col. 3, Lines 31-34).
However, Osumi does not explicitly disclose the processor constructs a training dataset for the artificial intelligence model to train the artificial intelligence model, and applies a test dataset to the artificial intelligence model to detect the dye mixing ratio.
Nevertheless, Nam discloses the processor constructs a training dataset for the artificial intelligence model to train the artificial intelligence model (The learning unit (170) can train a generation model that outputs optimal operating conditions and optimal mixing ratios when product information is input [0046]), and applies a test dataset to the artificial intelligence model to detect the dye mixing ratio (For example, the learning unit (170) can machine train a generation model using a dataset that includes the operating result value of the dyeing equipment (10) based on at least one of the operating conditions of the dyeing equipment (10) and the mixing ratio of the dyeing agent [0047]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Regarding Claim 7, Osumi and Nam disclose the claimed invention discussed in claim 6.
Osumi discloses the dataset includes at least one of an absorbance according to dye combination, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the training dataset (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of an answer sheet of the training dataset (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27).
However, Osumi does not explicitly disclose the training dataset includes at least one of an absorbance according to dye combination, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the training dataset, and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of an answer sheet of the training dataset.
Nevertheless, Nam discloses the training dataset includes at least one of an absorbance according to dye combination, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the training dataset (Data accumulated and stored on the server can be used as training data or learning data to calculate optimal equipment operating conditions and salt formulation ratios for the next product [0015]), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of an answer sheet of the training dataset (Data accumulated and stored on the server can be used as training data or learning data to calculate optimal equipment operating conditions and salt formulation ratios for the next product [0015]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to determine air speed measurements in two directions to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Regarding Claim 8, Osumi and Nam disclose the claimed invention discussed in claim 6.
Osumi discloses the dataset includes at least one of a buyer order absorbance, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the test dataset (as discussed above), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of the dataset (as discussed above).
However, Osumi does not explicitly disclose the test dataset includes at least one of a buyer order absorbance, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the test dataset, and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of the test dataset.
Nevertheless, Nam discloses the test dataset (as discussed above), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of the test dataset (The learning unit (170) can train a generation model that outputs optimal operating conditions and optimal mixing ratios when product information is input [0046]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Regarding Claim 11, Osumi discloses a method of detecting a dye mixing ratio, comprising: collecting, by a processor, computer color matching (CCM) colorimetric data for each dye concentration (The method of the present invention is further characterized in that, while determining the formulating ratio of the metallic or pearlescent pigment to the colorant or the formulating amount of the metallic or pearlescent pigment in the computer color matching of the coating composition, i.e. dye concentration, containing the metallic or pearlescent pigment, the predictive reproduction gonio-gonio-spectral reflectances is subjected to correction procedure comprising the steps of i) generating the gonio-spectral reflectance data of a coating comprising one or more metallic or pearlescent pigments or one or more metallic or pearlescent pigments and one or more colorants inclusive of a translucent pigment and the formulating amount or ratio data thereof or said two kinds of data and coating thickness data for taking into account the influence of under coating color or substrate color and coating thickness as measured for one or a plurality of coated plate samples, ii) storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching , Col. 4, Lines 5-27); converting, by the processor, the CCM colorimetric data for each dye concentration into absorbance data (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27) and detecting a dye mixing ratio that matches an absorbance graph of a buyer order, on the basis of an artificial intelligence model (In view of the above state of the art, the object of the present invention is to provide a method for computer-aided color matching that easily and accurately computes a formulating ratio of colorants to metallic or pearlescent pigments with the desired hue and luster characteristics of a metallic or pearlescent coating composition, i.e. buyer order, Col. 3, Lines 43-48).
However, Osumi does not explicitly disclose detecting a dye mixing ratio that matches an absorbance graph of a buyer order, on the basis of an artificial intelligence model.
Nevertheless, Nam discloses detecting a dye mixing ratio on the basis of an artificial intelligence model (The generating device (100) can automatically instruct the equipment to optimal operating conditions and optimal mixing ratios. To this end, the generating device (100) may be equipped with a generating model generated through machine learning [0037]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Regarding Claim 13, Osumi and Nam disclose the claimed invention discussed in claim 11.
Osumi discloses the processor converts a reflectance under buyer-order light source conditions into an absorbance (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27) and calculates a slope for each wavelength section of the absorbance data to use the calculated slope as rising and falling trend information of the absorbance graph (…storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching, Col. 4, Lines 19-26; …the incident energy of viewing light at wavelength .lambda. I.sub.o (.theta., .lambda.): the energy of light received at viewing angle .theta. and wavelength .lambda. C.sub.ori (.theta., .lambda.) the scattering orientation function of light provided by metallic or pearlescent pigment T.sub.trap (.lambda., x): the efficiency of trapping of viewing light at metallic or pearlescent pigment concentration, Col. 13, Lines 1-8), and calculates an absorbance area in a specific absorbance wavelength section to use the calculated area as information on a color intensity (…storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching, Col. 4, Lines 19-26; ; …the incident energy of viewing light at wavelength .lambda. I.sub.o (.theta., .lambda.): the energy of light received at viewing angle .theta. and wavelength .lambda. C.sub.ori (.theta., .lambda.) the scattering orientation function of light provided by metallic or pearlescent pigment T.sub.trap (.lambda., x): the efficiency of trapping of viewing light at metallic or pearlescent pigment concentration, Col. 13, Lines 1-8).
Regarding Claim 16, Osumi and Nam disclose the claimed invention discussed in claim 11.
Osumi discloses the processor constructs dataset (…a fuzzy deduction algorithm which, using gonio-spectral reflectance data of coated samples prepared in optional formulations using a plurality of colorants and a plurality of metallic or pearlescent pigments, sample formulation data, and sample coating condition data as stored in a memory of a computer ahead of time, Col. 8, Lines 11-17), and applies a dataset to detect the dye mixing ratio (Developed to accomplish the above object, the present invention is a method of determining a formulating ratio of a colorant to a metallic or pearlescent pigment or a formulating amount of a metallic or pearlescent, Col. 3, Lines 31-34).
However, Osumi does not explicitly disclose the processor constructs a training dataset for the artificial intelligence model to train the artificial intelligence model, and applies a test dataset to the artificial intelligence model to detect the dye mixing ratio.
Nevertheless, Nam discloses the processor constructs a training dataset for the artificial intelligence model to train the artificial intelligence model (The learning unit (170) can train a generation model that outputs optimal operating conditions and optimal mixing ratios when product information is input [0046]), and applies a test dataset to the artificial intelligence model to detect the dye mixing ratio (For example, the learning unit (170) can machine train a generation model using a dataset that includes the operating result value of the dyeing equipment (10) based on at least one of the operating conditions of the dyeing equipment (10) and the mixing ratio of the dyeing agent [0047]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Regarding Claim 17, Osumi and Nam disclose the claimed invention discussed in claim 16.
Osumi discloses the dataset includes at least one of an absorbance according to dye combination, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the training dataset (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of an answer sheet of the training dataset (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27).
However, Osumi does not explicitly disclose the training dataset includes at least one of an absorbance according to dye combination, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the training dataset, and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of an answer sheet of the training dataset.
Nevertheless, Nam discloses the training dataset includes at least one of an absorbance according to dye combination, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the training dataset (Data accumulated and stored on the server can be used as training data or learning data to calculate optimal equipment operating conditions and salt formulation ratios for the next product [0015]), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of an answer sheet of the training dataset (Data accumulated and stored on the server can be used as training data or learning data to calculate optimal equipment operating conditions and salt formulation ratios for the next product [0015]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to determine air speed measurements in two directions to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Regarding Claim 18, Osumi and Nam disclose the claimed invention discussed in claim 16.
Osumi discloses the dataset includes at least one of a buyer order absorbance, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the test dataset (as discussed above), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of the dataset (as discussed above).
However, Osumi does not explicitly disclose the test dataset includes at least one of a buyer order absorbance, a slope by wavelength, an absorbance area, RGB colors, a color intensity, and a K/S value as an input value of the test dataset, and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of the test dataset.
Nevertheless, Nam discloses the test dataset (as discussed above), and includes at least one of a dye code, a dye mixing ratio, and a total concentration as an output value of the test dataset (The learning unit (170) can train a generation model that outputs optimal operating conditions and optimal mixing ratios when product information is input [0046]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted to improve accuracy of the dye mixing ratio.
Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Osumi and Nam, and further in view of Fard et al. (US20120114234) hereinafter referred to as ‘Fard’.
Regarding Claim 2, Osumi and Nam disclose the claimed invention discussed in claim 1.
Osumi discloses the CCM colorimetric data for each dye concentration is a CCM colorimetric reflectance for each dye concentration (…storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching, Col. 4, Lines 19-26).
However, Osumi and Nam do not explicitly disclose the CCM colorimetric data for each dye concentration is a CCM colorimetric QuickTime extension (QTX) reflectance for each dye concentration.
Nevertheless, Fard discloses QuickTime extension (QTX) (An image is a set of one or more pixels. Images may take a variety of forms including bitmap, JPEG, Apple Icon Image, DNG, GIF, PDF, QuickTime Image, or other image file formats. According to one embodiment of the invention, an image may be associated with a color profile (e.g., an ICC color profile associated with a particular color space RGB (red, green, blue) [0026]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Fard to display dye concentration in a visual and interactive format while improving the accuracy of the dye mixing ratio.
Regarding Claim 12, Osumi and Nam disclose the claimed invention discussed in claim 11.
Osumi discloses the CCM colorimetric data for each dye concentration is a CCM colorimetric reflectance for each dye concentration (…storing said data in a memory of the computer in advance and iii) correcting for the difference between the stored data and the gonio-spectral reflectance predicted by the computer over the entire measuring wavelength range and entire angular range by a fuzzy logic (same as; a fuzzy deduction algorithm) to thereby improve the accuracy of color matching, Col. 4, Lines 19-26).
However, Osumi and Nam do not explicitly disclose the CCM colorimetric data for each dye concentration is a CCM colorimetric QuickTime extension (QTX) reflectance for each dye concentration.
Nevertheless, Fard discloses QuickTime extension (QTX) reflectance (An image is a set of one or more pixels. Images may take a variety of forms including bitmap, JPEG, Apple Icon Image, DNG, GIF, PDF, QuickTime Image, or other image file formats. According to one embodiment of the invention, an image may be associated with a color profile (e.g., an ICC color profile associated with a particular color space RGB (red, green, blue) [0026]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Fard to display dye concentration in a visual and interactive format while improving the accuracy of the dye mixing ratio.
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Osumi and Nam, and further in view of Lee et al. (US20100033721) hereinafter referred to as ‘Lee’.
Regarding Claim 4, Osumi and Nam disclose the claimed invention discussed in claim 1.
Osumi discloses the processor converts under buyer-order light source conditions ((In view of the above state of the art, the object of the present invention is to provide a method for computer-aided color matching that easily and accurately computes a formulating ratio of colorants to metallic or pearlescent pigments with the desired hue and luster characteristics of a metallic or pearlescent coating composition, i.e. buyer order, Col. 3, Lines 43-48) and calculates a color intensity and a K/S value on the basis of the sRGB values (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27).
However, Osumi does not explicitly disclose the processor converts XYZ values under buyer-order light source conditions into standard red, green, and blue (sRGB) values and calculates a color intensity and a K/S value on the basis of the sRGB values.
Nevertheless, Lee discloses the processor converts XYZ values under buyer-order light source conditions into standard red, green, and blue (sRGB) values (The XYZ values can be transformed to absolute values of RGB by using an sRGB transformation matrix [0055]) and calculates a color intensity and a K/S value on the basis of the sRGB values (Therefore, output values of the video sensor can be fitted to luminance and chromaticity values. For example, as shown in the figure, parameters a and b of a logarithmic function y.sub.i=a*log.sub.10(x.sub.i)+b are determined for each of the R, G, and B channels by using the least square fitting technique [0056]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Lee to acquire the correlation between the video sensor and the spectral radiation luminance meter and to improve accuracy of the dye mixing ratio.
Regarding Claim 14, Osumi and Nam disclose the claimed invention discussed in claim 11.
Osumi discloses the processor converts values under buyer-order light source conditions ((In view of the above state of the art, the object of the present invention is to provide a method for computer-aided color matching that easily and accurately computes a formulating ratio of colorants to metallic or pearlescent pigments with the desired hue and luster characteristics of a metallic or pearlescent coating composition, i.e. buyer order, Col. 3, Lines 43-48) and calculates a color intensity and a K/S value (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows. The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing, Col. 2, Lines 12-27).
However, Osumi does not explicitly disclose the processor converts XYZ values under buyer-order light source conditions into standard red, green, and blue (sRGB) values and calculates a color intensity and a K/S value on the basis of the sRGB values.
Nevertheless, Lee discloses the processor converts XYZ values under buyer-order light source conditions into standard red, green, and blue (sRGB) values (The XYZ values can be transformed to absolute values of RGB by using an sRGB transformation matrix [0055]) and calculates a color intensity and a K/S value on the basis of the sRGB values (Therefore, output values of the video sensor can be fitted to luminance and chromaticity values. For example, as shown in the figure, parameters a and b of a logarithmic function y.sub.i=a*log.sub.10(x.sub.i)+b are determined for each of the R, G, and B channels by using the least square fitting technique [0056]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Lee to acquire the correlation between the video sensor and the spectral radiation luminance meter and to improve accuracy of the dye mixing ratio.
Claims 5, 9-10,15, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Osumi and Nam, and further in view of Rich et al. (KR20110059734) hereinafter referred to as ‘Rich’.
Regarding Claim 5, Osumi and Nam disclose the claimed invention discussed in claim 1.
Osumi discloses the processor generates the absorbance on the basis of a ratio of dyes, generates an absorbance graph of a mixed dye that is calculated by summation when the dyes are mixed (as discussed above), and detects the dye mixing ratio that matches the absorbance of the buyer order (as discussed above).
However, Osumi and Nam do not explicitly disclose the processor generates the absorbance graph on the basis of a ratio of monochromatic dyes, generates an absorbance graph of a mixed dye that is calculated by summation when the monochromatic dyes are mixed, and detects the dye mixing ratio that matches the absorbance graph of the buyer order.
Nevertheless, Rich discloses the processor generates the absorbance graph on the basis of a ratio of monochromatic dyes (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0046]; Generally, in the development of custom spot color inks, there exists only a single combination of pigments that produces the correct color for both monochromatic tones and halftones between full tones and unprinted substrates [0021]), generates an absorbance graph of a mixed dye that is calculated by summation when the monochromatic dyes are mixed (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0055]), and detects the dye mixing ratio that matches the absorbance graph (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0055]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Rich to represent a mixture of the first and second dyes to improve accuracy of the dye mixing ratio.
Regarding Claim 9, Osumi and Nam disclose the claimed invention discussed in claim 6.
Osumi discloses the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data for the dye mixing ratio (as discussed above), calculates the number of possible combinations of dye mixing ratios (In the present invention, learning data necessary to reproduce a predicted color value are prepared ahead of time. The formulating ratios for the respective learning data are as follows, Col. 18, Lines 30-39) and calculates a combination for each combined dye ratio to construct the training dataset (In the present invention, learning data necessary to reproduce a predicted color value are prepared ahead of time. The formulating ratios for the respective learning data are as follows, Col. 18, Lines 30-39), and obtains the dye mixing ratio through a combination of the combined dye ratios (In the present invention, learning data necessary to reproduce a predicted color value are prepared ahead of time. The formulating ratios for the respective learning data are as follows, Col. 18, Lines 30-39) and calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model.
However, Osumi does not explicitly disclose the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data for the dye mixing ratio, calculates the number of possible combinations of dye mixing ratios and calculates a combination for each combined monochromatic dye ratio to construct the training dataset, and obtains the dye mixing ratio through a combination of the combined monochromatic dye ratios and calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model.
Nevertheless, Nam discloses and calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted and improve accuracy of the dye mixing ratio.
However, Osumi and Nam do not explicitly disclose the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data for the dye mixing ratio, calculates the number of possible combinations of dye mixing ratios and calculates a combination for each combined monochromatic dye ratio to construct the training dataset, and obtains the dye mixing ratio through a combination of the combined monochromatic dye ratios and calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model.
Nevertheless, Rich discloses the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data for the dye mixing ratio (as discussed above), and calculates a combination for each combined monochromatic dye ratio to construct the training dataset (as discussed above), and obtains the dye mixing ratio through a combination of the combined monochromatic dye ratios (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Rich to represent a mixture of the first and second dyes to improve accuracy of the dye mixing ratio.
Regarding Claim 10, Osumi and Nam disclose the claimed invention discussed in claim 1.
Osumi discloses the processor calculates the number of possible cases with a plurality of dye combinations, calculates the number of cases for a plurality of concentration intervals for the calculated number of cases (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows, Col. 2, Lines 12-20), then calculates an absorbance graph of a dye and an absorbance of the mixed dye for a dye mixing ratio presented in numbers in each case (The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing. This K/S is further transformed to reflectance to compute the formulating ratio of the colorants to the metallic or pearlescent pigment, Col. 2, Lines 21-30).
However, Osumi does not explicitly disclose the processor calculates the number of possible cases with a plurality of dye combinations, calculates the number of cases for a plurality of concentration intervals for the calculated number of cases, then calculates an absorbance graph of a monochromatic dye and an absorbance graph of the mixed dye for a dye mixing ratio presented in numbers in each case, generates a training dataset for the absorbance graph of the mixed dye, and uses the dye mixing ratio as an answer sheet.
Nevertheless, Nam discloses generates a training dataset for the absorbance graph of the mixed dye, and uses the dye mixing ratio as an answer sheet (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted and improve accuracy of the dye mixing ratio.
However, Osumi and Nam do not explicitly disclose the processor calculates the number of possible cases with a plurality of dye combinations, calculates the number of cases for a plurality of concentration intervals for the calculated number of cases, then calculates an absorbance graph of a monochromatic dye and an absorbance graph of the mixed dye for a dye mixing ratio presented in numbers in each case, generates a training dataset for the absorbance graph of the mixed dye, and uses the dye mixing ratio as an answer sheet.
Nevertheless, Rich discloses calculates an absorbance graph of a monochromatic dye and an absorbance graph of the mixed dye (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0055]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Rich to represent a mixture of the first and second dyes to improve accuracy of the dye mixing ratio.
Regarding Claim 15, Osumi and Nam disclose the claimed invention discussed in claim 11.
Osumi discloses the processor generates the absorbance on the basis of a ratio of dyes, generates an absorbance of a mixed dye that is calculated by summation when the dyes are mixed (as discussed above), and detects the dye mixing ratio that matches the absorbance of the buyer order (as discussed above).
However, Osumi and Nam do not explicitly disclose the processor generates the absorbance graph on the basis of a ratio of monochromatic dyes, generates an absorbance graph of a mixed dye that is calculated by summation when the monochromatic dyes are mixed, and detects the dye mixing ratio that matches the absorbance graph of the buyer order.
Nevertheless, Rich discloses the processor generates the absorbance graph on the basis of a ratio of monochromatic dyes (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0046]; Generally, in the development of custom spot color inks, there exists only a single combination of pigments that produces the correct color for both monochromatic tones and halftones between full tones and unprinted substrates [0021]), generates an absorbance graph of a mixed dye that is calculated by summation when the monochromatic dyes are mixed (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0055]), and detects the dye mixing ratio that matches the absorbance graph of the buyer order (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0055]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Rich to represent a mixture of the first and second dyes to improve accuracy of the dye mixing ratio.
Regarding Claim 19, Osumi and Nam disclose the claimed invention discussed in claim 16.
Osumi discloses the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data for the dye mixing ratio (as discussed above), calculates the number of possible combinations of dye mixing ratios (In the present invention, learning data necessary to reproduce a predicted color value are prepared ahead of time. The formulating ratios for the respective learning data are as follows, Col. 18, Lines 30-39) and calculates a combination for each combined dye ratio to construct the training dataset (In the present invention, learning data necessary to reproduce a predicted color value are prepared ahead of time. The formulating ratios for the respective learning data are as follows, Col. 18, Lines 30-39), and obtains the dye mixing ratio through a combination of the combined dye ratios (In the present invention, learning data necessary to reproduce a predicted color value are prepared ahead of time. The formulating ratios for the respective learning data are as follows, Col. 18, Lines 30-39) and calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model.
However, Osumi does not explicitly disclose the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data for the dye mixing ratio, calculates the number of possible combinations of dye mixing ratios and calculates a combination for each combined monochromatic dye ratio to construct the training dataset, and obtains the dye mixing ratio through a combination of the combined monochromatic dye ratios and calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model.
Nevertheless, Nam discloses calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted and improve accuracy of the dye mixing ratio.
However, Osumi and Nam do not explicitly disclose the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data for the dye mixing ratio, calculates the number of possible combinations of dye mixing ratios and calculates a combination for each combined monochromatic dye ratio to construct the training dataset, and obtains the dye mixing ratio through a combination of the combined monochromatic dye ratios and calculates a dye mixing concentration to construct an answer sheet for training to proceed with training of the artificial intelligence model.
Nevertheless, Rich discloses the processor converts a reflectance of the CCM colorimetric data for each dye concentration into an absorbance to use the absorbance as basic data (as discussed above), and calculates a combination for each combined monochromatic (as discussed above), and obtains the dye mixing ratio through a combination of the combined monochromatic dye ratios (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Rich to represent a mixture of the first and second dyes to improve accuracy of the dye mixing ratio.
Regarding Claim 20, Osumi and Nam disclose the claimed invention discussed in claim 11.
Osumi discloses the detecting of the dye mixing ratio, the processor calculates the number of possible cases with a plurality of dye combinations, calculates the number of cases for a plurality of concentration intervals for the calculated number of cases (In the CCM of a metallic or pearlescent coating composition, the base data samples used are formulation samples comprising the respective chromatic colorants to be used and a metallic or pearlescent pigment for matching a target color. Using those data as reference data representing the chromaticity of the chromatic colorants with respect to the metallic or pearlescent pigment, the predicted reflectance that will be obtained on mixing a plurality of chromatic colorants with the metallic or pearlescent pigment is computed as follows, Col. 2, Lines 12-20), then calculates an absorbance of a dye and an absorbance of the mixed dye for a dye mixing ratio presented in numbers in each case (The spectral reflectances of the base data as measured beforehand are transformed to the optical density K/S, which is the ratio of the absorption coefficient K to the scattering coefficient S of the colored layer using the Kubelka-Munk equation and the optical density K/S is computed by the 2-constant method which is based on Duncan's theoretical expression of color mixing. This K/S is further transformed to reflectance to compute the formulating ratio of the colorants to the metallic or pearlescent pigment, Col. 2, Lines 21-30).
However, Osumi does not explicitly disclose the processor calculates the number of possible cases with a plurality of dye combinations, calculates the number of cases for a plurality of concentration intervals for the calculated number of cases, then calculates an absorbance graph of a monochromatic dye and an absorbance graph of the mixed dye for a dye mixing ratio presented in numbers in each case, generates a training dataset for the absorbance graph of the mixed dye, and uses the dye mixing ratio as an answer sheet.
Nevertheless, Nam discloses generates a training dataset (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi with the teachings of Nam to output optimal operating conditions and optimal mixing ratios when product information is inputted and improve accuracy of the dye mixing ratio.
However, Osumi and Nam do not explicitly disclose the processor calculates the number of possible cases with a plurality of dye combinations, calculates the number of cases for a plurality of concentration intervals for the calculated number of cases, then calculates an absorbance graph of a monochromatic dye and an absorbance graph of the mixed dye for a dye mixing ratio presented in numbers in each case, generates a training dataset for the absorbance graph of the mixed dye, and uses the dye mixing ratio as an answer sheet.
Nevertheless, Rich discloses calculates an absorbance graph of a monochromatic dye and an absorbance graph of the mixed dye for a dye mixing ratio presented in numbers in each case (To create an ink with a halftone value intermediate between these two closest matches in the database, one converts the data to absorbance, as the absorbance curve is proportional to the colorant concentration by Beer's law of spectroscopy. If the absorbance data is then proportionally interpolated at each spectral point, in exemplary embodiments of the present invention a new absorbance curve can be obtained that is representative of the mixture of the colorants of the first ink and the second ink. The interpolated absorbance curve can then be converted back to reflectance factor, and its colorimetric coordinates can then be computed [0055]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Osumi and Nam with the teachings of Rich to represent a mixture of the first and second dyes to improve accuracy of the dye mixing ratio.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Takashi Hanamoto (US20090273819) discloses an image processing method for displaying a simulation image of an image formed on a print medium under a first light-source color on a display device under a second light-source color comprises an acquisition step of acquiring image data to be simulated in a format according to the second light-source color, a reflective color calculation step of calculating a reflective color obtained when the acquired image data is located under an achromatic light-source color.
Mickael Mheidle (US20070226919) discloses a method for dyeing or printing a textile fiber material is disclosed, which comprises the steps of providing a digital data processing device organizing reflectance curve data which are associated with the corresponding dye recipes.
Allan Rodrigues (US20070003961) discloses A process for refinishing or repainting a damaged paint area of a vehicle or part thereof using a computer-implemented method to determine a refinish paint formula that can be matched to the color of the original paint.
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/SHARAH ZAAB/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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