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 14 is objected to because of the following informalities: Claim 14 recites “the sample of grains” and its antecedent basis is unclear. Appropriate correction is required. The deficiency appears to be an oversight. The Examiner suggests amending “the sample of grains” to be “the grain sample” that has been introduced in the preamble.
Claim 14 is objected to because of the following informalities: Claim 14 recites “if the overlap amount meets the overlap threshold” and “if the overlap amount does not meet the overlap threshold” and the interpretation of used “if” may be unclear. Appropriate correction or clarification of the interpretation on the record is required. The recited “if” may indicate the presence of a contingent limitation, there is uncertainty as to whether the related contingent limitation is optional. The Examiner suggests replacing “if” with “in response to.” Claims 17-19 also use the limitation “if,” and they are also objected to. Appropriate correction or clarification of the interpretation on the record 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.
Claims 19-20 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.
Claim 19 recites, “defining the sizing polygon as a lower limit polygon representing an aperture size of an undersized sizing device and a separate upper limit polygon representing an aperture size of an oversized sizing device;”
It is unclear to the Examiner that same sizing polygon could be the “lower limit polygon” and “separate upper limit polygon” simultaneously and separately; and could be the “aperture size” of the “undersized sizing device” and “oversized sizing device” simultaneously and separately.
The specification does not provide guidance and also appears to contradict the claim language, and the specification states, “Furthermore, in the grain grading process, grains are cleaned before presenting to the graders. This cleaning process is comprised of multiple stages of filtration using standard sieve sizes. This filtration process is designed in such a way that any material which is either larger than an upper threshold size (too big) or smaller than a lower threshold size (too small), is filtered out of the grains.” Spec. Background.
For the purposes of art rejection, the Examiner is treating the limitation as “defining the sizing polygon as a lower limit polygon representing an aperture size of an undersized sizing device [[and]] or a separate upper limit polygon representing an aperture size of an oversized sizing device,” and the steps of (v-viii) as an alternative to the steps of (i-iv).
Claim 20 is rejected because it depends on Claim 19 and inherits the deficiency.
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.
Claims 14-15, 17-19, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Igathinathane et al. (“Sieveless particle size distribution analysis of particulate materials through computer vision”) in view of SHRIVASTAV et al. (US 20230069639 A1).
Regarding Claim 14, Igathinathane teaches A method of identifying objects in a
), the method comprising:
receiving an image of the sample of grains (“We proposed and utilized a computer vision with image processing as an alternative approach; wherein a user-coded Java ImageJ plugin was developed to evaluate PSD based on length of particles.” Igathinathane Abstract.);
processing the image to identify object polygons in the image representing individual grain objects
“We proposed and utilized a computer vision with image processing as an alternative approach; wherein a user-coded Java ImageJ plugin was developed to evaluate PSD based on length of particles.” Igathinathane Abstract.
“The square or circular openings of standard sieves, in the strictest sense, will only allow ‘width-based separation’ of particles. That is, these openings truly restrict particles of width larger than the sieve opening dimension irrespective of particle orientation with respect to the openings (Igathinathane et al., 2008a).” Igathinathane 3. Characteristics of mechanical sieving. Igathinathane Fig. 3.
“For instance: a sieve simulation with three sieves will divide the particles into four groups, the first three groups represent particles retained on the three sieves and the fourth group
represents particles passed through the 3rd sieve and that collected in pan.” Igathinathane 2.8. Effect of number of sieves by simulation and statistical analysis.
“Test samples utilized were ground biomass obtained from . . . Basmati rice.” Igathinathane Abstract.);
defining a sizing polygon representing an aperture size of the sizing apertures of the sizing device (
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“For instance: a sieve simulation with three sieves will divide the particles into four groups, the first three groups represent particles retained on the three sieves and the fourth group
represents particles passed through the 3rd sieve and that collected in pan.” Igathinathane 2.8. Effect of number of sieves by simulation and statistical analysis.
Igathinathane Fig. 3 shows a sizing device, a sieve device.
The visual representation as shown in Fig. 3 including the sieve opening corresponds to the sizing polygon.); and
for each object polygon (Igathinathane Fig. 3 Particle tipped on edge and “falling through.”):
(i) positioning the object polygon relative to the sizing polygon to maximize an intersection of the object polygon with the sizing polygon (
Note in Igathinathane Fig. 3 the particle polygon is rotated so that the particle polygon can “fall through” the sieve polygon in the Fig. 3.
Intersection has been maximized, because the particle object falls through and every part of the particle polygon in Fig. 3 intersect with the sieve by going through the sieve.);
(ii) calculating an overlap amount between the object polygon and the sizing polygon (
“For instance: a sieve simulation with three sieves will divide the particles into four groups, the first three groups represent particles retained on the three sieves and the fourth group represents particles passed through the 3rd sieve and that collected in pan. The dimensions of the equally spaced simulated sieves were obtained by dividing the total particle length range by 4 and allotting sieve dimensions progressively. In essence, the sieve simulation is simply mathematically grouping numbers indicating particle lengths based on number ranges indicating selected virtual sieve dimensions.” Igathinathane 2.8. Effect of number of sieves by simulation and statistical analysis.
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Fig. 3, Fig 8 and Igathinathane 2.8. “length-based separation” show that the simulation assumes that if the length of the particle is smaller than the width of a simulated sieve, the particle “falls through” the sieve.
Therefore, the overlap amount is 100% (when falling through) by determining/calculating that the length of the particle is smaller than the size of a simulated sieve. The overlap amount is 0% (when not falling through) by determining/calculating the length of the particle is greater than or equal to the size of the simulated sieve. The calculation is done by comparing, a form of calculation, the length of the particle and the size of the sieve.)
Igathinathane does not explicitly teach; however, SHRIVASTAV teaches:
processing the image to identify object polygons in the image representing individual grain objects and impurity objects (
SHRIVASTAV states, “Further, differentiate the plurality of elements, post confirming the sample element mixture is of the grain type, wherein the differentiation is based on a lower threshold and an upper threshold of an Inter Quartile Range (IQR) of a perimeter metric corresponding to the perimeter of each of the plurality of elements to segregate the plurality of elements as: a first set of elements having lower size impurity in the sample element mixture, a second set of elements having a target grain perimeter range identified for the grain type, and a third set of elements having a higher size impurity.” SHRIVASTAV ¶ 17.
The impurity objects are mapped to elements having a higher size impurity and/or elements having lower size impurity.);
(iii) comparing the overlap amount to an overlap threshold (SHRIVASTAV ¶ 17 teaches lower bound and higher bound thresholds. After the combination of Igathinathane and SHRIVASTAV, these thresholds become Igathinathane’s overlap amount.); and
(iv) determining the object polygon to be an impurity object if the overlap amount meets the overlap threshold or determining the grain polygon to be a grain polygon for grading if the overlap amount does not meet the overlap threshold (SHRIVASTAV ¶ 17 teaches the determination of elements having a higher size impurity and/or elements having lower size impurity and/or target grain side based on Igathinathane in view of SHRIVASTAV’s overlap threshold and corresponding simulated sieve’s aperture.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine SHRIVASTAV’s impurity classification with primary reference Igathinathane. One of ordinary skill in the art would be motivated to provide more accurate grain grading by identifying impurities. “Digitization has penetrated into the agricultural domain, wherein myriad of digital applications assist traditional processes and also often bring in complete automation in certain agricultural or agro-based systems. Grain grading is one of the critical and challenging task in the agro-domain as it requires expertise. Grain grading analysis refers determining grain variety, various types of adulterants and their levels to predict the quality of grain.” SHRIVASTAV ¶ 3.
Regarding Claim 15, Igathinathane in view of SHRIVASTAV teaches The method according to claim 14 including performing grading analysis (SHRIVASTAV Fig. 2B 212 a)) on the object polygons that are determined to be grain polygons (second set of elements of target grains) while excluding the object polygons that are determined to be non-grain polygons (excluding the first and third sets of elements of impurities according to SHRIVASTAV Fig. 2B 201, 212 a)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine SHRIVASTAV’s impurity classification with primary reference Igathinathane. One of ordinary skill in the art would be motivated to provide more accurate grain grading by identifying impurities.
Regarding Claim 17, Igathinathane in view of SHRIVASTAV teaches The method according to claim 14 wherein the sizing polygon represents a lower limit polygon for identifying undersized impurity objects (elements having lower size impurity) and wherein the method includes determining the object polygon to be a non-grain polygon if the overlap amount is greater than the overlap threshold (elements having a lower size impurity that passes though the sieve when the impurities are small enough; its corresponding overlap amount is 100%, great than the overlap threshold that could be 80%) (
SHRIVASTAV states, “Further, differentiate the plurality of elements, post confirming the sample element mixture is of the grain type, wherein the differentiation is based on a lower threshold and an upper threshold of an Inter Quartile Range (IQR) of a perimeter metric corresponding to the perimeter of each of the plurality of elements to segregate the plurality of elements as: a first set of elements having lower size impurity in the sample element mixture, a second set of elements having a target grain perimeter range identified for the grain type, and a third set of elements having a higher size impurity.” SHRIVASTAV ¶ 17.
SHRIVASTAV ¶ 17 teaches the determination of elements having a higher size impurity and/or elements having lower size impurity and/or target grain side based on Igathinathane in view of SHRIVASTAV’s overlap threshold and corresponding simulated sieve’s aperture.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine SHRIVASTAV’s impurity classification with primary reference Igathinathane. One of ordinary skill in the art would be motivated to provide more accurate grain grading by identifying impurities.
Regarding Claim 18, Igathinathane in view of SHRIVASTAV teaches The method according to claim 14
wherein the sizing polygon represents an upper limit polygon for identifying oversized impurity objects (elements having higher size impurity) and wherein the method includes determining the object polygon to be a non-grain polygon if the overlap amount is less than the overlap threshold (elements having a higher size impurity that fail to pass though the sieve when the impurities are too big; its corresponding overlap amount is 0%, less than the overlap threshold that could be 80%)) (
SHRIVASTAV states, “Further, differentiate the plurality of elements, post confirming the sample element mixture is of the grain type, wherein the differentiation is based on a lower threshold and an upper threshold of an Inter Quartile Range (IQR) of a perimeter metric corresponding to the perimeter of each of the plurality of elements to segregate the plurality of elements as: a first set of elements having lower size impurity in the sample element mixture, a second set of elements having a target grain perimeter range identified for the grain type, and a third set of elements having a higher size impurity.” SHRIVASTAV ¶ 17.
SHRIVASTAV ¶ 17 teaches the determination of elements having a higher size impurity and/or elements having lower size impurity and/or target grain side based on Igathinathane in view of SHRIVASTAV’s overlap threshold and corresponding simulated sieve’s aperture.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine SHRIVASTAV’s impurity classification with primary reference Igathinathane. One of ordinary skill in the art would be motivated to provide more accurate grain grading by identifying impurities.
Regarding Claim 19, Igathinathane in view of SHRIVASTAV teaches The method according to claim 14 further comprising:
defining the sizing polygon as a lower limit polygon representing an aperture size of an undersized sizing device and a separate upper limit polygon representing an aperture size of an oversized sizing device (
[BRI on the record]
The Claim has been rejected under 112(b). For the purposes of art rejection, the Examiner is treating the limitation as “defining the sizing polygon as a lower limit polygon representing an aperture size of an undersized sizing device [[and]] or a separate upper limit polygon representing an aperture size of an oversized sizing device,” and the steps of (v-viii) as an alternative to the steps of (i-iv).
[Mapping Analyses]
SHRIVASTAV states, “Further, differentiate the plurality of elements, post confirming the sample element mixture is of the grain type, wherein the differentiation is based on a lower threshold and an upper threshold of an Inter Quartile Range (IQR) of a perimeter metric corresponding to the perimeter of each of the plurality of elements to segregate the plurality of elements as: a first set of elements having lower size impurity in the sample element mixture, a second set of elements having a target grain perimeter range identified for the grain type, and a third set of elements having a higher size impurity.” SHRIVASTAV ¶ 17.
SHRIVASTAV ¶ 17 teaches the determination of elements having a higher size impurity and/or elements having lower size impurity and/or target grain side based on Igathinathane in view of SHRIVASTAV’s overlap threshold and corresponding simulated sieve’s aperture.
Igathinathane 2.8; Fig. 3., showing a polygon, a graphical representation, of a sieve aperture that could correspond to undersized sizing device or configured to correspond to an oversized sizing device depending on the simulated sieve.);
for each object polygon:
(i) positioning the object polygon relative to the lower limit polygon to maximize an intersection of the object polygon with the lower limit polygon (see Claim 14’s analyses for a similar limitation, except that the recited “sizing polygon” in Claim 14 is the lower limit polygon. The combination of Igathinathane in view of SHRIVASTAV teaches that the lower limit polygon is mapped to a simulated lower limit sieve to separate elements of lower size impurity. Igathinathane 2.8; Fig. 3.);
(ii) calculating a first overlap amount between the object polygon and the lower limit polygon (see Claim 14’s analyses for a similar limitation, except that the recited “sizing polygon” in Claim 14 is the lower limit polygon and the recited “overlap amount” is the first overlap amount. The combination of Igathinathane in view of SHRIVASTAV teaches that the lower limit polygon is mapped to a simulated lower limit sieve to separate elements of lower size impurity. Igathinathane 2.8; Figs. 3, 8.
The calculation specific to the lower limit polygon produces first overlap amount.);
(iii) comparing the first overlap amount to a first overlap threshold; (iv) determining the object polygon to be a non-grain polygon if the first overlap amount is greater than the first overlap threshold (SHRIVASTAV ¶ 17 teaches lower bound and higher bound thresholds. After the combination of Igathinathane and SHRIVASTAV, these thresholds become Igathinathane’s overlap amount. The use of the simulated sieve, elements of lower size impurity are determined.);
(v) positioning the object polygon relative to the upper limit polygon to maximize an intersection of the object polygon with the upper limit polygon;(vi) calculating a second overlap amount between the object polygon and the upper limit polygon; (vii) comparing the second overlap amount to a second overlap threshold; (viii) determining the object polygon to be a non-grain polygon if the second overlap amount is less than the second overlap threshold (
see Claim 14’s analyses for a similar limitation, except that the recited “sizing polygon” in Claim 14 is the upper limit polygon. The same analyses apply here.
SHRIVASTAV states, “Further, differentiate the plurality of elements, post confirming the sample element mixture is of the grain type, wherein the differentiation is based on a lower threshold and an upper threshold of an Inter Quartile Range (IQR) of a perimeter metric corresponding to the perimeter of each of the plurality of elements to segregate the plurality of elements as: a first set of elements having lower size impurity in the sample element mixture, a second set of elements having a target grain perimeter range identified for the grain type, and a third set of elements having a higher size impurity.” SHRIVASTAV ¶ 17.
SHRIVASTAV ¶ 17 teaches the determination of elements having a higher size impurity and/or elements having lower size impurity and/or target grain side based on Igathinathane in view of SHRIVASTAV’s overlap threshold and corresponding simulated sieve’s aperture.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine SHRIVASTAV’s impurity classification with primary reference Igathinathane. One of ordinary skill in the art would be motivated to provide more accurate grain grading by identifying impurities.
Regarding Claim 21, Igathinathane in view of SHRIVASTAV teaches A system comprising: a memory storing programming instructions; and at least one processor arranged to execute the programming instructions so as to be configured to execute the method according to claim 14 (Igathinathane Abstract, stating “We proposed and utilized a computer vision with image processing as an alternative approach;.” SHRIVASTAV ¶¶ 19, 54, 63, 65.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine SHRIVASTAV’s impurity classification with primary reference Igathinathane. One of ordinary skill in the art would be motivated to make computation faster with modern computers.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Igathinathane in view of SHRIVASTAV as applied to Claim 19, in further view of JYUMONJI (US 20190036325 A1).
Regarding Claim 20, Igathinathane in view of SHRIVASTAV teaches The method according to claim 19.
Igathinathane in view of SHRIVASTAV does not explicitly teach; but JYUMONJI wherein the first overlap threshold and the second overlap threshold are identical to one another (“The upper and lower limit threshold values a and the upper and lower limit threshold values b may be identical to each other or the ranges may partially overlap each other.” JYUMONJI ¶ 94.).
It would have been “Obvious to try” – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success. There are two identified and predictable solutions: the thresholds are the same or different. JYUMONJI ¶ 94. There is a reasonable expectation of success. For example, if the first and second overlap thresholds are the same and are 80%, the algorithms according to Igathinathane in view of SHRIVASTAV would work properly.
Allowable Subject Matter
Claim 16 is objected to as being dependent upon a rejected base claim, but would be allowable if (1) rewritten in independent form including all of the limitations of the base claim and any intervening claims, and (2) Applicant addresses other rejections and objections if applicable.
The following is a statement of reasons for the indication of allowable subject matter: Claim 16 is distinguished from Igathinathane in view of SHRIVASTAV because of the additional limitations recited in the Claim:
including maximizing said intersection of the object polygon with the sizing polygon by iteratively repositioning the object polygon relative to the sizing polygon by tuning translation and rotation of the object polygon to maximize overlap with the sizing polygon.
Igathinathane and SHRIVASTAV teach length-based separation, width-based separation, and perimeter-based separation, which do not teach the claimed features regarding a separation technique recited in Claim 16
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
GARZUKH et al. (RU 2667637 C1):
“Particle width is a preferred parameter of particle size according to the present invention, since this parameter is most closely related to physical screening using screening through a sieve. A particle with a width smaller than the virtual size of the sieve opening can pass through this sieve, even if the length of such a particle is greater than the width. Thus, the terms ‘particle size’ and ‘sieve diameter’ essentially have the same meaning in the context of the invention and should be understood interchangeably in the context of the present invention.”
Although GARZUKH has teaching that overlaps with Igathinathane, it is not as strong as the primary reference.
WILDZEISZ et al. (WO 2021084030 A1):
“Using the particle width values, mass fractions within specific particle size ranges may then be derived, or cumulative mass fractions of all particles smaller than a specific particle size x (i.e. the fraction(s) which would pass the 'virtual sieve’ of diameter x), as well as the weighted arithmetic mean particle size, and the D10, D50 and D90 values (i.e. the particle size of the 'virtual sieve’ which is passed by a mass fraction of 10 %, 50 % and 90 % of the particles, respectively); similar to usual sieve analysis, however with a far higher precision. In other words, a particle size distribution with a given D50 or D90 value, for example, means that 50 % or 90 %, respectively, of the particles are considered to have the given particle size value.”
Although WILDZEISZ teaches virtual sieve analysis, it does not teach identifying impurity objects.
Xie et al. (CN 116300769 A)
“As a preferred mode of the present invention, the stack storage component further comprises a grain sieving unit, the grain sieving unit comprises a driving piece, a connecting piece, a multi-layer screen, two ends of the connecting piece are respectively connected with the driving end of the driving, the multi-layer screen is connected, the driving piece drives the connecting piece to drive the multi-layer screen to move; the multi-layer screen comprises a screen, an aperture adjusting piece, a plurality of screen arranged in array along the length direction of the connecting piece; the aperture adjusting member is mounted on the screen; the aperture size of the screen is adjusted by the aperture adjusting member.”
Xie provides context information about a grain sieve system with adjustable apertures.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHENGXI LIU whose telephone number is (571)270-7509. The examiner can normally be reached M-F 9 AM - 5 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kee Tung can be reached at 571-272-7794. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ZHENGXI LIU/Primary Examiner, Art Unit 2611
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