DETAILED ACTION
Claims 1-20 are pending.
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 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.
Claim(s) 1, 4-5, 8, 11-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maalouf et al. (US 2019/0087943) in view of Arnison et al. (US 2015/0146994).
Claim 1, Maalouf teaches A method for estimating a spatial resolution of a digital image acquisition system, the method comprising:
acquiring a digital image (i.e. imaged) of an edge feature (i.e. target) using a digital image acquisition system (p. 0029);
computing a modeled image (i.e. synthetic image) of the edge feature using a mathematical model (i.e. digital model) (p. 0048); and
“adjusting one or more parameters in the mathematical model (i.e. digital model) to minimize a difference between the digital image of the edge feature and the modeled image of the edge feature to obtain one or more optimized model parameters” (i.e. minimum difference between digital mode and target) of the digital image acquisition system (p. 0034, 0048-0049).
Maalouf is silent regarding the specific feature of:
“wherein the one or more optimized model parameters include a variance parameter characterizing blur introduced by the digital image acquisition system”;
“determining a spatial frequency response of the digital image acquisition system from the variance parameter”.
Arnison teaches the specific feature of:
“wherein the one or more optimized model parameters include a variance parameter (i.e. relative blur) characterizing blur introduced by the digital image acquisition system” (i.e. blur introduced by defocus) (p. 0007);
“determining a spatial frequency response of the digital image acquisition system from the variance parameter” (i.e. spectral ratio) (p. 0007).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided blur variance as taught by Arnison to the system of Maloof to determine a depth value of pixels (p. 0006-0007).
Claim 4, 16 Maalouf teaches The method of claim 1, wherein the difference between the digital image of the edge feature and the modeled image of the edge feature comprises a mean square error (i.e. average OTF) (p. 0059-0064).
Claim 5 is analyzed and interpreted as an apparatus of claim 1.
Claim 8, Maalouf teaches The system of claim 5, wherein the processor is further configured to:
automatically adjust a setting on the digital camera in response to one or more optimized model parameters in the mathematical model (i.e. adjusting camera within working zone until minimal difference) (p. 0029-0032, 0049);
cause the digital camera to take an additional digital image of the object including the edge feature (i.e. iterative imaging until minimal difference) (p. 0049);
compute an additional modeled image of the edge feature (i.e. iterative readjustment of every modeled image) (p. 0049); and
adjust the one or more optimized model parameters in the mathematical model to minimize a difference between the additional digital image and the additional modeled image of the edge feature to obtain one or more updated optimized parameters in the mathematical model (i.e. iterative readjustment of every modeled image) (p. 0049).
Claim 11, Maloof is not entirely clear in teaching The method of claim 1, further comprising adjusting an operating parameter of the digital image acquisition system in response to the spatial frequency response.
Arnison teaches teaching The method of claim 1, further comprising adjusting an operating parameter of the digital image acquisition system in response to the spatial frequency response (i.e. adjusting distance to account for blur) (p. 0089-0096).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided blur variance as taught by Arnison to the system of Maloof to determine a depth value of pixels (p. 0006-0007).
Claim 12 and 17, Maloof is not entirely clear in teaching The method of claim 11, further comprising:
comparing the variance parameter or the spatial frequency response to a threshold value; and
adjusting the operating parameter of the digital image acquisition system, based on comparing the variance parameter or the spatial frequency response to the threshold value,
wherein the operating parameter comprises one or more of a camera focus setting, a sensor saturation setting, an illumination direction setting, an illumination color setting, an illumination intensity setting, an illumination power setting, a temperature condition, or a humidity condition.
Arnison teaches The method of claim 11, further comprising:
comparing the variance parameter or the spatial frequency response to a threshold value (i.e. threshold on local variance) (p. 0151); and
adjusting the operating parameter of the digital image acquisition system, based on comparing the variance parameter or the spatial frequency response to the threshold value (i.e. adjusting distance to account for blur) (p. 0089-0096, 0151),
wherein the operating parameter comprises one or more of a camera focus setting (i.e. focus) (p. 0089-0096), a sensor saturation setting, an illumination direction setting, an illumination color setting, an illumination intensity setting, an illumination power setting, a temperature condition, or a humidity condition.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided blur variance as taught by Arnison to the system of Maloof to determine a depth value of pixels (p. 0006-0007).
Claim 13, Maloof is silent regarding The method of claim 1, wherein the mathematical model comprises a point spread function model of the digital image acquisition system and the variance parameter comprises a Gaussian approximation of the point spread function model.
Arnison teaches The method of claim 1, wherein the mathematical model comprises a point spread function model (i.e. PSF) of the digital image acquisition system and the variance parameter comprises a Gaussian approximation of the point spread function model (p. 0090).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided blur variance as taught by Arnison to the system of Maloof to determine a depth value of pixels (p. 0006-0007).
Claim 14, Maloof teaches The method of claim 1, wherein the variance parameter comprises an optimized variance parameter corresponding to a minimum difference between the digital image of the edge feature and the modeled image of the edge feature (i.e. minimum difference between digital mode and target) (p. 0034, 0048-0049).
Claim 15, Maloof teaches The method of claim 1, wherein adjusting the one or more parameters of the mathematical model comprises iteratively varying candidate values for the variance parameter (i.e. iterative readjustment of every modeled image) (p. 0049).
Claim 18 is analyzed and interpreted with respect to the features included in claims 8 and 14.
Claim(s) 2, 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maalouf et al. (US 2019/0087943) in view of Arnison et al. (US 2015/0146994), and further in view of Seo (US 2019/0236787).
Claim 2, Maalouf teaches the method of claim 1, wherein the mathematical model comprises an edge function that includes a point spread function of the digital image acquisition system (p. 0018).
Maalouf is silent regarding the specific feature of:
“wherein the point spread function of the digital image acquisition system is estimated with a univariate analytic even function or a Gaussian function”.
Seo teaches the specific feature of:
“wherein the point spread function of the digital image acquisition system is estimated with a univariate analytic even function or a Gaussian function” (p. 0007).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided Gaussian function as taught by Seo to the system of Maalouf to estimate edge and edge blur parameters (p. 0007).
Claim 6 is analyzed and interpreted as an apparatus of claim 2.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maalouf et al. (US 2019/0087943) in view of Arnison et al. (US 2015/0146994), and further in view of Janssen et al. (US 10014158).
Claim 3, Maalouf is silent regarding the method of claim 1, further comprising estimating an angular orientation of the edge feature, wherein the one or more parameters in the mathematical model comprise a gain parameter, an offset parameter, a Gaussian variance, and an image shift.
Janssen teaches The method of claim 1, further comprising estimating an angular orientation of the edge feature, wherein the one or more parameters in the mathematical model comprise a gain parameter (i.e. gain correction), an offset parameter (i.e. offsets), a Gaussian variance, and an image shift (i.e. positional shift) (col. 4-5, lines 62-34).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided orientation features as taught by Janssen to the system of Maalouf to achieve corrective enhancement (col. 4-5, lines 62-34).
Claim(s) 7, 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maalouf et al. (US 2019/0087943) in view of Arnison et al. (US 2015/0146994), and further in view of Krishnaswamy et al. (US 2013/0044185).
Claim 7, Maalouf is silent regarding the system of claim 5, wherein the processor is further configured to compute the spatial frequency response of the digital camera using the one or more optimized parameters in the mathematical model.
Krishnaswamy teaches the system of claim 5, wherein the processor is further configured to compute the spatial frequency response of the digital camera using the one or more optimized parameters in the mathematical model (i.e. determine spatial frequency) (p. 0039, claim 10).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided spatial frequency calculation as taught by Krishnaswamy to the system of Maalouf to provide to recover spatial frequencies (p. 0039).
Claim 9 is analyzed and a combination of claim 1, 7-8.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maalouf et al. (US 2019/0087943) in view of Arnison et al. (US 2015/0146994), and further in view of Krishnaswamy et al. (US 2013/0044185), and further in view of Seo (US 2019/0236787).
Claim 10 is analyzed and interpreted with respect to claim 2.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maalouf et al. (US 2019/0087943) in view of Arnison et al. (US 2015/0146994), and further in view of Michlig Gonzalez et al. (US 2017/0367588).
Claim 19, Maloof is silent regarding The method of claim 1, further comprising estimating an angular orientation of the edge feature by fitting a line to centroids of rows in a region of interest of the digital image corresponding to the edge feature.
Michlig Gonzalez teaches The method of claim 1, further comprising estimating an angular orientation of the edge feature by fitting a line to centroids of rows in a region of interest of the digital image corresponding to the edge feature (i.e. drawn manually for a ROI) (p. 0081).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided manually drawing ROIs as taught by Michlig Gonzalez to the system of Maloof for alignment performance (p. 0081).
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maalouf et al. (US 2019/0087943) in view of Arnison et al. (US 2015/0146994), and further in view of Michlig Gonzalez et al. (US 2017/0367588), and further in view of Janssen et al. (US 10014158).
Claim 20, Maloof is silent regarding The method of claim 19, further comprising computing the modeled image of the edge feature based on the angular orientation.
Jannssen teaches The method of claim 19, further comprising computing the modeled image of the edge feature based on the angular orientation (i.e. positional shift) (col. 4-5, lines 62-34).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have provided orientation features as taught by Janssen to the system of Maalouf to achieve corrective enhancement (col. 4-5, lines 62-34).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Claims 1-20 are rejected.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20230005108 A1 Gopalkrishna; Vijay Kumar Baikampady et al. – replacing blurred screen text
US 20200313768 A1 Cox; Jason et al. – optical communication with grey level local variance
US 20190228506 A1 DeWeert; Michael J. et al. – spatial frequency and deblurring
US 9516237 B1 Goyal; Dushyant et al. – high spatial frequencies with sharp edges
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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MUSHFIKH I. ALAM
Primary Examiner
Art Unit 2426
/MUSHFIKH I ALAM/Primary Examiner, Art Unit 2426 8/25/2026
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