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 .
Claim Objections
Claim 5 is objected to because of the following informalities: it appears that there is a misspelling of “chromacity”, the Examiner believes it should spell “chromaticity”. Appropriate correction is required.
Claim 8 is objected to because of the following informalities: the claims states “wherein the control unit is configured to control the light source by switching on and off the at least one illuminant of the light source at at least one defined illumination time point for a defined illumination duration”. It is unclear if the “at at” is supposed to just have one “at” or if it’s supposed to be “or at”. Appropriate correction is required.
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.
Claim 10 is 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.
Claim 10 recites the limitation "the flicker cycle". There is insufficient antecedent basis for this limitation in the claim. The Examiner believes it should state “a flicker cycle”. Appropriate correction is required.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 2, 4, and 6-9 are rejected under 35 U.S.C. 103 as being unpatentable over Rein et al., US 2023/0078604 A1 (Rein) and further in view of Gatto et al., US 2020/0042817 A1 (Gatto).
Regarding claim 1, Rein teaches a system for object recognition (a system, including a detector, for object recognition) (Fig. 1; Abstract and [0212]), said system comprising:
- a light source (illumination source 114) (Fig. 1; [0213-0214]) configured to illuminate a scene (configured to project at least one illumination pattern on at least one area 116; scene) (Fig. 1; [0213]) in which at least one object (having at least one object 112 located within a scene) (Fig. 1; [0213]) having object specific properties (a reflectivity) ([0110-0111]) is present (the beam profile information may comprise information about a material property of said surface point or region having reflected the illumination feature) ([0076] and [0107-0111]), wherein the light source comprises at least one illuminant (wherein the illumination source comprises at least one light source) (Fig. 1; [0215]);
- a sensor unit (optical sensor 120) (Fig. 1; [0221-0222]) for acquiring data (for acquiring image data) ([0221-0222]) on object specific properties (material property based on reflectivity) ([0109-0111]) upon illumination of the scene (configured to project at least one illumination pattern on at least one area 116; scene) (Fig. 1; [0213]) by the light source (illumination source 114) (Fig. 1; [0213-0214]) for each object (having at least one object 112 located within a scene) (Fig. 1; [0213]) having object specific properties (the beam profile information may comprise information about a material property of said surface point or region having reflected the illumination feature) ([0076] and [0107-0111]) and being present in the scene (wherein the object is present in the scene) (Fig. 1; [0213]),
wherein the sensor unit (optical sensor 120) (Fig. 1; [0221-0222]) includes at least one color sensitive sensor (wherein the optical sensor may be sensitive in the visible spectral range from 500nm to 780nm) (Fig. 1; [0223]) and at least one camera filter (at least one first filter element 128) (Fig. 1; [0230]) selectively blocking the reflected light and allowing passage of reflected light (wherein the filter element 128 can be configured for transmitting light in a small spectral range) (Fig. 1; [0230]) originating from illuminating the scene (configured to project at least one illumination pattern on at least one area 116; scene) (Fig. 1; [0213]) with the light source (illumination source 114) (Fig. 1; [0213-0214]) into the at least one color sensitive sensor (wherein the optical sensor may be sensitive in the visible spectral range from 500nm to 780nm) (Fig. 1; [0223]), the at least one camera filter being positioned optically intermediate the scene and the color sensitive sensor(s) (wherein the filter 128 is positioned between the scene 116 with object 112 and the optical sensor 120) (Fig. 1; [0213] and [0221]);
- a data storage medium comprising a plurality of digital representations of pre-defined objects (database 136 comprising a list and/or table of predefined and/or predetermined material properties) (Fig. 1; [0260]);
- and a processing unit (evaluation device 124 using at least one processor) (Fig. 1; [0056] and [0227]) in communication with the sensor unit and the light source (the evaluation device 124 connected in communication with detector 110 (which includes optical sensor 120 and illumination source 114)) (Fig. 1; [0266]), the processing unit programmed to:
optionally determine further object specific luminescence properties from the acquired data on object specific reflectance and/or luminescence properties, and
determine the object(s) based on
the data acquired on object specific properties and/or the determined further object specific properties (wherein the evaluation device 124 uses the reflective properties to determine the material property and shape and/or size of the object for object identification) (Fig. 1; [0259-0264]) and
the digital representations of pre-defined objects (using the database 136 comprising a list and/or table of predefined and/or predetermined material properties) (Fig. 1; [0264] and [0266]).
Rein teaches determining the beam profile information for each of the reflection features by analysis of their beam profiles ([0076]). However, Rein does not explicitly teach object specific “reflectance and/or luminescence” properties.
Gatto teaches a system to determine a reflectance feature of an object (such as liquid) (Abstract); and wherein the object specific reflectance properties can be obtained and compared with images that are prestored in a database to identify the object ([0051-0052]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Rein to include obtaining reflectance properties since by adding the additional information it increases the accuracy of the object identification (Gatto; [0003]).
Regarding claim 2, Rein teaches wherein the at least one illuminant comprises at least one LED, or wherein all illuminants comprise at least one LED (wherein the illumination source 114 can be at least one light-emitting diode) (Fig. 1; [0215]).
Regarding claim 4, Gatto teaches wherein the digital representation of each pre-defined object comprises pre-defined object specific reflectance and/or luminescence properties optionally associated with the object (wherein the pre-defined object specific reflectance properties associated with the object) ([0051-0052]).
Regarding claim 6, Gatto teaches wherein the processing unit (the circuitry may for example be implemented by a processor) ([0033]) is programmed to determine the object(s) based on the data acquired on object specific reflectance and/or luminescence properties and/or the optionally determined further object specific reflectance and/or luminescence properties (determining the objects reflectance properties using the circuitry for images) ([0050-0052]) and the digital representations of pre-defined objects (predefined reflectance spectra stored in a database) ([0052]) by calculating the best matching reflectance and/or luminescence properties and obtaining the object(s) assigned to the best matching reflectance and/or luminescence properties (comparing the calculated reflectance spectrum with the predefined reflectance spectra and selecting a reflectance spectrum having the strongest similarity and the object can be identified) ([0052]).
Regarding claim 7, Rein teaches further comprising a control unit (control unit 126) (Fig. 1; [0227]) configured to control the light source and/or the sensor unit (wherein the control unit 126 may be configured for controlling the optical sensor 120 and/or the illumination source 114) (Fig. 1; [0227]).
Regarding claim 8, Rein teaches wherein the control unit (control unit 126) (Fig. 1; [0227]) is configured to control the light source by switching on and off the at least one illuminant of the light source at at least one defined illumination time point for a defined illumination duration (wherein the control unit 126 can be configured for adapting and/or adjusting the illumination time from frame to frame; different illumination times) ([0227-0228]).
Regarding claim 9, Rein teaches wherein the control unit (control unit 126) (Fig. 1; [0227]) is configured to control the sensor unit by switching on and off the at least one color sensitive sensor at defined acquisition time points and/or under defined lighting conditions for a defined acquisition duration (the control unit 126 may be configured for controlling the optical sensor 120, such as the frame rate) ([0227]).
Claim(s) 3 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Rein et al., US 2023/0078604 A1 (Rein), Gatto et al., US 2020/0042817 A1 (Gatto), and further in view of Gorman et al., US 2022/0163634 A1 (Gorman).
Regarding claim 3, Rein teaches wherein each camera filter (at least one first filter element 128) (Fig. 1; [0230]) of the sensor unit (optical sensor 120) (Fig. 1; [0221-0222]) to spectral light emitted by the illuminant(s) (configured to project at least one illumination pattern; projecting spectral light) (Fig. 1; [0213-0215]) of the light source (illumination source 114) (Fig. 1; [0213-0214]). Gatto teaches a system including circuitry configured to determine a reflectance feature of a liquid based on reflectance image data generated based on multispectral image data (Abstract).
However, neither explicitly teaches that the filter “is matched” to the spectral light emitted.
Gorman teaches an active illumination apparatus includes an emission source configured to illuminate a field of view (Abstract); and wherein the passband of the detector-side filter may be configured to vary so as to match or otherwise correspond to the wavelengths of light output from the emission sources at each field angle of the FOV ([0074]).
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 combination of prior arts to include matching the filter with the emitted light since it can reduce the detection of radiation/light from other sources (such as solar or ambient light sources) (Gorman; [0005]).
Regarding claim 16, Gorman teaches wherein the at least one illuminant comprises at least one narrowband LED, or wherein all illuminants comprise at least one are narrowband LED (using illumination sources having a relatively narrow spectral bandwidth) ([0005] and [0080]) (wherein the illumination sources/emitter(s) can be LEDs) ([0082] and [0085]).
Claim(s) 5 is rejected under 35 U.S.C. 103 as being unpatentable over Rein et al., US 2023/0078604 A1 (Rein), Gatto et al., US 2020/0042817 A1 (Gatto), and further in view of Zuzak et al., US 2010/0056928 A1 (Zuzak).
Regarding claim 5, Rein teaches wherein the processing unit (evaluation device 124 using at least one processor) (Fig. 1; [0056] and [0227]) is programmed to determine the further object specific properties from the data acquired on object specific properties (wherein the evaluation device 124 uses the reflective properties to determine the material property and shape and/or size of the object for object identification) (Fig. 1; [0259-0264]) by
- generating differential data by subtracting data of the scene acquired by at least one color sensitive sensor under ambient lightning and data of the scene acquired by at least one color sensitive sensor under ambient lightning and illumination by the light source (generating differential data by performing background subtraction; the evaluation device 124 may be adapted to remove influences from background light from the reflection beam profile, for example, by an imaging without further illumination) (Fig. 1; [0243]),
Rein teaches determining the beam profile information for each of the reflection features by analysis of their beam profiles ([0076]). However, Rein does not explicitly teach object specific “reflectance and/or luminescence” properties.
Gatto teaches a system to determine a reflectance feature of an object (such as liquid) (Abstract); and wherein the object specific reflectance properties can be obtained and compared with images that are prestored in a database to identify the object ([0051-0052]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Rein to include obtaining reflectance properties since by adding the additional information it increases the accuracy of the object identification (Gatto; [0003]).
However, neither explicitly teaches “- determining the regions of luminescence in the generated differential data and - transforming the RGB values of the differential data into rg chromacity values or determining the luminescence spectral pattern and/or the reflective spectral pattern for the determined regions of luminescence”.
Zuzak teaches a hyperspectral imaging system (Abstract); wherein - determining the regions of luminescence (wherein the reflected one or more single wavelength electromagnetic radiations may include luminescence) ([0036], [0043], and [0048]) in the generated differential data (wherein the image obtained can be obtained by subtracting the raw image against its background) ([0228]) and - transforming the RGB values of the differential data into rg chromacity values or determining the luminescence spectral pattern and/or the reflective spectral pattern for the determined regions of luminescence (determining the luminescence reflected from the determined one or more objects) ([0043] and [0048]).
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 combination of prior arts to include detecting a luminescence since it increases the information gathered thus increasing the accuracy of detecting the type of object (Zuzak; [0014] and [0427]).
Claim(s) 10-13 are rejected under 35 U.S.C. 103 as being unpatentable over Rein et al., US 2023/0078604 A1 (Rein), Gatto et al., US 2020/0042817 A1 (Gatto), and further in view of Tamada et al., JP 2003069895 A (Tamada).
Regarding claim 10, Rein teaches wherein the control unit 126 can be configured for adapting and/or adjusting the illumination time from frame to frame; different illumination times ([0227-0228]). Gatto teaches a system to determine a reflectance feature of an object (such as liquid) (Abstract).
However, neither explicitly teaches “wherein the defined acquisition time points and/or the defined acquisition durations are dependent on the flicker cycle of the ambient light sources present in the scene”.
Tamada teaches an image processing apparatus for controlling the image pickup processing by the image pickup means, and an external light detecting means for detecting ambient light outside the apparatus (p. 2; Section [0005], 1st paragraph); phase calculating means for obtaining the phase of the outside light from the outside light data detected by the outside light detecting means (p. 2; Section [0005], 1st paragraph); and wherein the defined acquisition time points and/or the defined acquisition durations are dependent on the flicker cycle of the ambient light sources present in the scene (wherein the acquisition times of photographing is made to agree with the optional flicker phase) (p. 1; Abstract and p. 2; last paragraph to page 3, 1st paragraph).
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 combination of prior arts to include being dependent on a flicker cycle since it allows the brightness of the captured image to be improved (Tamada; p. 1, last paragraph).
Regarding claim 11, Tamada teaches wherein the defined acquisition time points are set via phase-locking such that each color sensitive sensor is always switched on at the same part of the flicker cycle (wherein the photographing is made to agree with the flicker phase) (p. 1; Abstract).
Regarding claim 12, Tamada teaches wherein the defined acquisition duration corresponds to a whole number integer multiple of the flicker cycle (wherein the flicker cycle has a sampling period; the sampling period can be 4) (Figs. 7a and 7B; p. 6; 10th-11th paragraphs).
Regarding claim 13, Tamada teaches wherein the whole number integer multiple of the flicker cycle is 1/60 of a second and/or 2/60 of a second and/or 3/60 of a second and/or 4/60 of a second or wherein the whole number integer multiple of the flicker cycle is 1/50 of a second and/or 2/50 of a second and/or 3/50 of a second and/or 4/50 of a second (wherein data for 5 seconds can be used for detection, and detection is performed at a 0.2Hz; however, the frequency detection resolution depends on the number of data to be sampled and the sampling period which can be set) (Figs. 7a and 7B; p. 6; 10th-14th paragraphs).
Claim(s) 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Rein et al., US 2023/0078604 A1 (Rein), Gatto et al., US 2020/0042817 A1 (Gatto), and further in view of Ortiz Egea et al., US 10,996,169 B2 (Ortiz Egea).
Regarding claim 14, Rein teaches a computer-implemented method (processing device including one or more processors) ([0056]) for recognizing at least one object (a system, including a detector, for object recognition) (Fig. 1; Abstract and [0212]) having specific properties (a reflectivity) ([0110-0111]) in a scene (within a scene) ([0213]), the method comprising:
(i) illuminating - with a light source (illumination source 114) (Fig. 1; [0213-0214]) comprising at least one illuminant - the scene (configured to project at least one illumination pattern on at least one area 116; scene) (Fig. 1; [0213]) in which the least one object (having at least one object 112 located within a scene) (Fig. 1; [0213]) having object specific properties (a reflectivity) ([0110-0111]) is present (wherein an object 112 is located within the scene) (Fig. 1; [0213]),
(ii) acquiring - with a sensor unit (optical sensor 120) (Fig. 1; [0221-0222]) – data (for acquiring image data) ([0221-0222]) on the object specific properties (material property based on reflectivity) ([0109-0111]) upon illuminating the scene (configured to project at least one illumination pattern on at least one area 116; scene) (Fig. 1; [0213]) with the light source (illumination source 114) (Fig. 1; [0213-0214]) for each object having (having at least one object 112 located within a scene) (Fig. 1; [0213]) object specific properties (the beam profile information may comprise information about a material property of said surface point or region having reflected the illumination feature) ([0076] and [0107-0111]) and being present in the scene (wherein the object is present in the scene) (Fig. 1; [0213]), wherein the sensor unit (optical sensor 120) (Fig. 1; [0221-0222]) includes at least one color sensitive sensor (wherein the optical sensor may be sensitive in the visible spectral range from 500nm to 780nm) (Fig. 1; [0223]) and at least one camera filter (at least one first filter element 128) (Fig. 1; [0230]) selectively blocking the reflected light and allowing passage of reflected light (wherein the filter element 128 can be configured for transmitting light in a small spectral range) (Fig. 1; [0230]) originating from illuminating the scene (configured to project at least one illumination pattern on at least one area 116; scene) (Fig. 1; [0213]) with the light source (illumination source 114) (Fig. 1; [0213-0214]) into the at least one color sensitive sensor (wherein the optical sensor may be sensitive in the visible spectral range from 500nm to 780nm) (Fig. 1; [0223]), the at least one camera filter being positioned optically intermediate the scene and the sensor(s) (wherein the filter 128 is positioned between the scene 116 with object 112 and the optical sensor 120) (Fig. 1; [0213] and [0221]);
(iii) optionally determining - with a computer processor - further object specific properties from the data acquired in step (ii);
(iv) providing to the computer processor (evaluation device 124 using at least one processor) (Fig. 1; [0056] and [0227]) via a communication interface (the evaluation device 124 connected in communication with detector 110 (which includes optical sensor 120 and illumination source 114)) (Fig. 1; [0266]) digital representations of pre-defined objects (using the database 136 comprising a list and/or table of predefined and/or predetermined material properties) (Fig. 1; [0264] and [0266]);
(v) determining - with the computer processor (evaluation device 124 using at least one processor) (Fig. 1; [0056] and [0227]) - the object(s) based on data acquired on object specific properties and/or the optionally determined further object specific properties (wherein the evaluation device 124 uses the reflective properties to determine the material property and shape and/or size of the object for object identification) (Fig. 1; [0259-0264]) and the provided digital representations of pre-defined objects (using the database 136 comprising a list and/or table of predefined and/or predetermined material properties) (Fig. 1; [0264] and [0266]), and
(vi) optionally providing via a communication interface the determined object(s) (the evaluation device can be connected to or may comprise at least one further data processing device that may be used for one or more of displaying, visualizing, analyzing, distributing, communicating or further processing of information, such as information obtained by the optical sensor and/or by the evaluation device) ([0059]).
Rein teaches determining the beam profile information for each of the reflection features by analysis of their beam profiles ([0076]). However, Rein does not explicitly teach object specific “reflectance and/or luminescence” properties.
Gatto teaches a system to determine a reflectance feature of an object (such as liquid) (Abstract); and wherein the object specific reflectance properties can be obtained and compared with images that are prestored in a database to identify the object ([0051-0052]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Rein to include obtaining reflectance properties since by adding the additional information it increases the accuracy of the object identification (Gatto; [0003]).
However, neither explicitly teaches “wherein each illuminant of the light source has a full-width- half-max (FWHM) of 1 to 50 nm”.
Ortiz Egea teaches a camera system that includes one or more spectral illuminators, a tunable optical filter, and a sensor array to acquire one or more images of a scene (Abstract); and wherein each illuminant of the light source has a full-width- half-max (FWHM) of 1 to 50 nm (each spectral illuminator may have a full width at half maximum (FWHM) of 20 nm) (col. 12, lines 56-59).
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 combination of prior arts to include a light source with FWHM since it allows the system to accurately determine a true spectral fluorescent signature of the substance that is minimally or not biased by ambient light (Ortiz Egea; col. 6, lines 60-63) and thus increase the accuracy of identification (Ortiz Egea; col. 6, lines 63-67).
Regarding claim 15, see the rejection made to claim 14, as well as prior art Gatto for a non-transitory computer-readable storage medium (non-transitory computer-readable recording medium) ([0152]), the computer-readable storage medium including instructions (non-transitory computer-readable recording medium is provided that stores therein a computer program product) ([0152]) that when executed by a computer (executed by a processor) ([0152]), cause the computer to perform the steps according to the method of claim 14 (causes the processor to cause the methods described) ([0152]), for they teach all the limitations within this claim.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Robinson, US 2018/0053038 A1: teaches methods for computing, on a per material and per hyperspectrally imaged scene basis, an optimal set of spectrally filtering pass bands for detecting target materials in the scenes, and cueing multispectral imaging of the scenes with the set of pass bands (Abstract).
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J VANCHY JR whose telephone number is (571)270-1193. The examiner can normally be reached Monday - Friday 9am - 5pm.
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/MICHAEL J VANCHY JR/Primary Examiner, Art Unit 2666 Michael.Vanchy@uspto.gov