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 .
Priority
Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Claim Amendments
Acknowledgment of receiving amendments to the claims, which were received by the Office on 06/23/2026. Examiner notes: The claim amendments filed on 06/23/2026 do not correctly track changes from the claims filed on 01/22/2025.
Response to Arguments
Applicant's arguments filed 06/23/2026 have been fully considered but they are not persuasive.
In that remarks, applicant argues in substance:
Applicant argues: “Saito relates to a technique for acquiring training data for a machine learning model used to detect defective pixels that have not been registered at the time of manufacture. (Satio, para. [0007].) With respect to defective pixels registered in advance in correction information, Saito's first correction part 2 performs correction. With respect to defective pixels not registered in advance in the correction information, inference part 4 estimates such defective pixels using a machine learning model, and then the second correction part 6 performs correction in the same manner as the first correction part 2. (Satio, paras. [0029], [0031], [0041]-[0043].) Saito also describes, as a modification, that inference part 4 may estimate defective pixels that are registered in the correction information. (Satio, para. [0040].) However, in Saito, inference part 4, which uses the machine learning model, merely estimates defective pixels and does not perform correction of defective pixels. Thus, Saito neither discloses nor suggests correcting defective pixels using a machine learning model. Furthermore, Saito does not contemplate, with respect to detection and correction of defective pixels, not using the first correction part 2, nor does Saito contemplate not using inference part 4 and the second correction part 6. Thus, Satio fails to teach or suggest, " a first processing unit capable of applying the predetermined processing," "a second processing unit capable of applying the predetermined processing," and "the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit, or is executed in a shared manner by both the first processing unit and the second processing unit," as recited by amended independent claim 1.”
Examiner’s Response: Examiner respectfully disagrees. The second processing unit configured to apply the predetermined processing using a machine learning model is considered to include inference part 4, a second storage part 5 and a second correction part 6. The second correction part performs correction of defective pixels using second correction information inferred from the inference part 4 which use the machine learning model (Saito, Paragraphs 0083-0086). Therefore, Saito teaches a second processing unit correcting defective pixels using a machine learning model.
Further, Examiner agrees “Saito does not contemplate, with respect to detection and correction of defective pixels, not using the first correction part 2, nor does Saito contemplate not using inference part 4 and the second correction part 6.” However, this is not seen to prevent disclosure of the claim language "a first processing unit capable of applying the predetermined processing," "a second processing unit capable of applying the predetermined processing," and "the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit, or is executed in a shared manner by both the first processing unit and the second processing unit,". For example, the control unit executes predetermined processing of the first processing unit depending on whether Step S721 occurs and executes predetermined processing of the second processing unit depending on whether Step S743 occurs. Therefore, the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit. That is, claim language does not require only one of the first processing unit and the second processing unit to execute the predetermined processing.
Further, claim recites “the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit, or is executed in a shared manner by both the first processing unit and the second processing unit”. Therefore, the limitation is seen to be met since the process of Figure 6 may be seen to be both the first processing unit and the second processing unit executing the predetermined processing in a shared manner (Fig. 6A, 6C and 6D, Paragraphs 0075-0078 and 0083-0085).
Applicant argues: “Lee relates to an image sensor, and more particularly, to an image sensor for correcting pixel values of defective pixels based on at least one of pixel values of neighboring pixels of the defective pixels and deep learning. (Lee, para [0002].) Specifically, Lee discloses correcting defective pixels using first defective pixel corrector 310, which does not use a machine learning model, when the defective pixel is isolated, and using second defective pixel corrector 320, which uses a machine learning model, when the defective pixels form a cluster. (Lee, paras [0051]- [0054].) In Lee, information regarding defective pixels is stored in advance in ISP 300. (Lee, para. [0049].) However, Lee neither discloses nor suggests that first defective pixel corrector 310 or second defective pixel corrector 320 performs detection of defective pixels, and in particular neither discloses nor suggests detecting defective pixels using a machine learning model as required by amended independent claim 1. Furthermore, Lee uses a defective pixel corrector corresponding to the type of each defective pixel, on a pixel-by-pixel basis, rather than selecting, for defective pixels as a whole, whether to use one of the defective pixel correctors or both of the defective pixel correctors. Thus, Lee fails to teach or suggest, " a first processing unit capable of applying the predetermined processing," "a second processing unit capable of applying the predetermined processing," and "the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit, or is executed in a shared manner by both the first processing unit and the second processing unit," as recited by amended independent claim 1.”
Examiner’s Response: Examiner respectfully disagrees. The first processing unit may be considered to be DPC1 310 and pre-processor 350. Therefore, the first processing unit performs the predetermined processing “including (i) processing related to detection of defective pixels included in an image sensor used to capture the image data and (ii) processing related to correction of signals of the detected defective pixels”. Similarly, the second processing unit may be considered to be DPC2 320 and pre-processor 350. Therefore, the second processing unit performs the predetermined processing “including (i) processing related to detection of defective pixels included in an image sensor used to capture the image data and (ii) processing related to correction of signals of the detected defective pixels”.
Claim language recites “predetermined processing including (i) processing related to detection of defective pixels included in an image sensor used to capture the image data and (ii) processing related to correction of signals of the detected defective pixels”, “a first processing unit capable of applying the predetermined processing without using any machine learning model; a second processing unit capable of applying the predetermined processing using a machine learning model”. Claim language does not explicitly require the first processing unit and the second processing unit to perform detection of defective pixels. Therefore, if the first processing unit and the second processing unit are considered to only be DPC1 310 and DPC2 320 respectively, the limitations are met since correction of the defective pixels may be considered to be processing related to detection of defective pixels.
Claim language does not require “selecting, for defective pixels as a whole, whether to use one of the defective pixel correctors or both of the defective pixel correctors”. Lee teaches wherein the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit (Lee, Paragraph 0097-0099), or is executed in a shared manner by both the first processing unit and the second processing unit (Lee, Paragraphs 0104-0107, If both types of defective pixels occur, correction is executed in a shared manner.).
Applicant argues: “Moreover, and notwithstanding the above, dependent claim 8 recites, "wherein the control unit determines whether the second processing unit is to execute the predetermined processing, based on a shooting scene of the image data or a shooting mode during capture of the image data." As discussed below Satio and Lee fail to teach or suggest every feature of dependent claim 8.
Satio, as discussed above, relates to an image pickup apparatus. The Office Action relies on step S721 of Saito to reject dependent claim 8. However, Saito does not teach or suggest selecting a correction unit that performs detection and correction of defective pixels, including the cited portion. Moreover, Saito is silent regarding shooting scene of image data or a shooting mode used during image capture. Therefore, dependent claim 8 is patentable over Satio.
Lee, as discussed above, relates to an image sensor. The Office Action relies on step S1230 of Lee to reject dependent claim 8. As best understood by Applicant, Lee requires the use of second defective pixel corrector 320 when the defective pixels form a cluster. However, Lee is silent regarding shooting scene of image data or a shooting mode used during image capture. Therefore, dependent claim 8 is patentable over Lee.”
Examiner’s Response: Examiner respectfully disagrees. Claim language does not limit what “based on a shooting scene of the image data” requires. A shooting scene of the image data may be considered to be capturing the image. The control units of both Saito and Lee do not control the second processing unit to execute the predetermined processing when there is no captured image and controls the second processing unit to execute the predetermined processing when an image is captured.
Applicant argues: “Dependent claim 10 recites, "wherein the control unit determines that the second processing unit is to execute the predetermined processing in a case where a temperature of the image processing apparatus is greater than or equal to a threshold or a shutter speed used to capture the image data is longer than or equal to a threshold." As discussed below Satio and Lee fail to teach or suggest every feature of dependent claim 10.
Satio, as discussed above, relates to an image pickup apparatus. The Office Action asserts that "Saito, Fig. 6D, Step S762, the control unit determines the second processing unit is to execute the predetermined processing at Step S762 regardless of the temperature. Therefore, in a case where a temperature of the image processing apparatus is greater than or equal to an arbitrary threshold, the control unit determines that the second processing unit is to execute the predetermined processing at Step S762." (Office Action, page 9.) However, Saito is silent regarding temperature of the apparatus. Moreover, although the Office Action interprets regards second correction part 6 described in step S762 as corresponding to the claimed second processing unit, the second correction part 6 is unrelated to the machine learning model and therefore does not correspond to the claimed second processing unit. Therefore, dependent claim 10 is patentable over Satio.
Lee, as discussed above, relates to an image sensor. The Office Action relies on step S 1230 of Lee to reject dependent claim 10. Lee is silent regarding temperature of the apparatus. Moreover, although the Office Action regards second defective pixel corrector 320 as corresponding to the claimed second processing unit, second defective pixel corrector 320 performs only correction and therefore does not correspond to the claimed second processing unit. Therefore, dependent claim 10 is patentable over Lee.”
Examiner’s Response: Examiner respectfully disagrees. Claim language does not require measuring, detecting, or comparing the temperature of the apparatus. Claim language merely recites “in a case where a temperature of the image processing apparatus is greater than or equal to a threshold”. The limitation is met since the apparatus may perform the predetermined processing by the second processing unit in a case where the temperature of the apparatus is greater than an arbitrary threshold.
With regard to Saito, the second processing unit is considered to be the inference part 4, second storage part 5, and second correction part 6. Predetermined processing by the inference part 4 is directly related to the machine learning model. Further, predetermined processing by the second correction part 6 described in step S762 is considered to be related to the machine learning model since the correction is based on the output from the inference part 4.
With regard to Lee, the second processing unit may be considered to be DPC2 320 and pre-processor 350 or only DPC2 320 as stated above. DPC2 320 is considered to perform predetermined processing including (i) processing related to detection of defective pixels included in an image sensor used to capture the image data and (ii) processing related to correction of signals of the detected defective pixels.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-8 and 10-12 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Saito (US 2021/0243395 A1).
Regarding claim 1, Saito teaches an image processing apparatus (Saito, Fig. 1) that executes, on image data (Saito, Paragraph 0020, “image signal”), predetermined processing including (i) processing related to detection of the defective pixels (Saito, Paragraphs 0025 and 0031, Defective pixels are detected from the first storage part and by the inference part.) included in an image sensor (Saito, Fig. 1, solid-state image pickup device 1) used to capture the image data and (ii), processing related to correction of signals of the detected defective pixels (Saito, Paragraphs 0065, 0078 and 0083 and 0085, Defective pixels are corrected in the first and second correction parts.), comprising one or more processors that execute one or more programs stored in a memory and thereby function as (Saito, Paragraphs 0008, 0091 and 0104):
a first processing unit capable of applying the predetermined processing without using any machine learning model (Saito, Fig. 1, first correction part 2, Paragraphs 0024-0027);
a second processing unit capable of applying the predetermined processing using a machine learning model (Saito, Fig. 1, inference part 4, a second storage part 5, a second correction part 6, Paragraphs 0033-0043); and
a control unit configured to control operations of the first processing unit and the second processing unit (Saito, Fig. 1, Control Part 7, Paragraph 0058),
wherein the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit (Saito, Fig. 6, Steps 6A and 6C-6D, Paragraphs 0075-0078 and 0083-0085, The control unit executes predetermined processing of the first processing unit depending on whether Step S721 occurs. The control unit executes predetermined processing of the second processing unit depending on whether Step S743 occurs.), or is executed in a shared manner by both the first processing unit and the second processing unit (Saito, Fig. 6A, 6C and 6D, Paragraphs 0075-0078 and 0083-0085, The control unit executes predetermined processing in a shared manner depending on whether Step S721 occurs.).
Regarding claim 2, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein
if the predetermined processing is executed in a shared manner by both the first processing unit and the second processing unit, the control unit controls the first processing unit and the second processing unit to execute the processing related to detection and the processing related to correction in a shared manner (Saito, Fig. 6A and 6C-6D, Steps S724 and S744-S745, Paragraphs 0065, 0078 and 0083, Defective pixels are detected from the first storage part and by the inference part.).
Regarding claim 3, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the control unit controls the first processing unit to execute the processing related to detection (Saito, Fig. 6A, Steps S721 and S724, Paragraphs 0075 and 0078, The first processing unit detects defective pixels using information from the first storage part. Further, all processing by the first processing unit may be considered to be related to detection.) and the second processing unit to execute the processing related to correction (Saito, Fig. 6D, Step S762, Paragraph 0085).
Regarding claim 4, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the processing related to detection includes processing related to detection of a first type of defective pixel generated in a process for manufacturing the image sensor (Saito, Paragraph 0024), and processing related to detection of a second type of defective pixel generated after the manufacturing of the image sensor (Saito, Paragraphs 0030-0031), and
the control unit controls the first processing unit to execute the processing related to detection of the first type of defective pixel (Saito, Fig. 6A, Steps S721 and S724, Paragraphs 0075 and 0078) and the second processing unit to execute the processing related to detection of the second type of defective pixel and the processing related to correction (Saito, Figs. 6C-6D, Paragraphs 0083-0085).
Regarding claim 5, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the processing related to detection includes processing related to detection of a first type of defective pixel generated in a process for manufacturing the image sensor (Saito, Paragraph 0024), and processing related to detection of a second type of defective pixel generated after the manufacturing of the image sensor (Saito, Paragraphs 0030-0031), and
the control unit controls one of the first processing unit and the second processing unit to execute the processing related to detection of the first type of defective pixel based on stored information on the first type of defective pixel (Saito, Fig. 6A, Steps S721 and S742, Paragraphs 0024, 0075 and 0078).
Regarding claim 6, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the processing related to detection includes processing related to detection of a first type of defective pixel generated in a process for manufacturing the image sensor (Saito, Paragraph 0024), and processing related to detection of a second type of defective pixel generated after the manufacturing of the image sensor (Saito, Paragraphs 0030-0031), and
in a case where the second processing unit is to execute the predetermined processing, the control unit controls the second processing unit so as to execute the processing related to detection of the first type of defective pixel based on stored information on the first type of defective pixel, and execute the processing related to detection of the second type of defective pixel and the processing related to correction are executed using the machine learning model (Saito, Figs. 6C-6D, The predetermined processing performed by the second processing unit is the detection of the second type of defective pixel and correction using the machine learning model. The predetermined processing performed by the second processing unit is also considered to be related to detection of the first type of defective pixel based on stored information on the first type of defective pixel since the processing performed by the second processing unit occurs after detection and correction of the first type of defective pixel.).
Regarding claim 7, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the processing related to detection includes processing related to detection of a first type of defective pixel generated in a process for manufacturing the image sensor (Saito, Paragraph 0024), and processing related to detection of a second type of defective pixel generated after the manufacturing of the image sensor (Saito, Paragraphs 0030-0031), and
in a case where the second processing unit is to execute the predetermined processing, the control unit controls the second processing unit so as to execute, using the machine learning model, the processing related to detection of the first type of defective pixel, the processing related to detection of the second type of defective pixel, and the processing related to correction (Saito, Figs. 6C-6D, The predetermined processing performed by the second processing unit is the detection of the second type of defective pixel and correction using the machine learning model. The predetermined processing performed by the second processing unit is also considered to be related to detection of the first type of defective pixel based on stored information on the first type of defective pixel since the processing performed by the second processing unit occurs after detection and correction of the first type of defective pixel.).
Regarding claim 8, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the control unit determines whether the second processing unit is to execute the predetermined processing, based on a shooting scene of the image data (Saito, Fig. 6A, Step S721, The second processing unit executes the predetermined processing based on when/if a first image signal is captured (a shooting scene of the image data).) or a shooting mode during capture of the image data.
Regarding claim 10, Saito teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the control unit determines that the second processing unit is to execute the predetermined processing in a case where a temperature of the image processing apparatus is greater than or equal to a threshold (Saito, Fig. 6D, Step S762, The control unit determines the second processing unit is to execute the predetermined processing at Step S762 regardless of the temperature. Therefore, in a case where a temperature of the image processing apparatus is greater than or equal to an arbitrary threshold, the control unit determines that the second processing unit is to execute the predetermined processing at Step S762.) or a shutter speed used to capture the image data is longer than or equal to a threshold.
Regarding claim 11, Saito teaches an image capture apparatus (Saito, Fig. 1) comprising:
an image sensor (Saito, Fig. 1, solid-state image pickup device 1); and
an image processing apparatus that executes predetermined processing (Saito, Paragraphs 0029 and 0041) on image data (Saito, Paragraph 0020, “image signal”) obtained using the image sensor (Saito, Fig. 1, Elements 2-8), wherein the predetermined processing includes (i) processing related to detection of defective pixels included in the image sensor (Saito, Paragraphs 0025 and 0031, Defective pixels are detected from the first storage part and by the inference part.) and (ii) processing related to correction of signals of the detected defective pixels (Saito, Paragraphs 0065, 0078 and 0083 and 0085, Defective pixels are corrected in the first and second correction parts.),
wherein the image processing apparatus comprising one or more processors that execute one or more programs stored in a memory and thereby function as (Saito, Paragraphs 0008, 0091 and 0104):
a first processing unit capable of applying the predetermined processing without using any machine learning model (Saito, Fig. 1, first correction part 2, Paragraphs 0024-0027);
a second processing unit capable of applying the predetermined processing using a machine learning model (Saito, Fig. 1, inference part 4, a second storage part 5, a second correction part 6, Paragraphs 0033-0043); and
a control unit configured to control operations of the first processing unit and the second processing unit (Saito, Fig. 1, Control Part 7, Paragraph 0058),
wherein the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit (Saito, Fig. 6, Steps 6A and 6C-6D, Paragraphs 0075-0078 and 0083-0085, The control unit executes predetermined processing of the first processing unit depending on whether Step S721 occurs. The control unit executes predetermined processing of the second processing unit depending on whether Step S743 occurs.), or is executed in a shared manner by both the first processing unit and the second processing unit (Saito, Fig. 6A, 6C and 6D, Steps S724 and S762, Paragraphs 0075-0078 and 0083-0085, The control unit executes predetermined processing in a shared manner depending on whether Step S721 occurs.).
Regarding claim 12, Saito teaches an image processing method (Saito, Fig. 6) of executing predetermined processing on image data (Saito, Paragraph 0020, “image signal”) by an image processing apparatus (Saito, Fig. 1),
wherein the predetermined processing including (i) processing related to detection of defective pixels (Saito, Paragraphs 0025 and 0031, Defective pixels are detected from the first storage part and by the inference part.) included in an image sensor (Saito, Fig. 1, solid-state image pickup device 1) used to capture the image data and (ii) processing related to correction of signals of the detected defective pixels (Saito, Paragraphs 0065, 0078 and 0083 and 0085, Defective pixels are corrected in the first and second correction parts.), and
wherein the image processing apparatus comprises a first processing unit capable of applying the predetermined processing without using machine learning model (Saito, Fig. 1, first correction part 2, Paragraphs 0024-0027), and a second processing unit capable of applying the predetermined processing using a machine learning model (Saito, Fig. 1, inference part 4, a second storage part 5, a second correction part 6, Paragraphs 0033-0043),
the image processing method comprising:
controlling the first processing unit and the second processing unit (Saito, Fig. 1, Control Part 7, Paragraph 0058),
wherein the controlling includes:
controlling one of the first processing unit and the second processing unit to execute the predetermined processing (Saito, Fig. 6, Steps S724 and S762, Paragraphs 0078 and 0085, Both the first processing unit and the second processing unit to execute the predetermined processing.), or
controlling both the first processing unit and the second processing unit to execute the predetermined processing a shared manner (Saito, Fig. 6A, 6C and 6D, Steps S724 and S762, Paragraphs 0078 and 0085, The control unit executes predetermined processing in a shared manner.).
Claim(s) 1-3, 8 and 10-12 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Lee et al. (US 2024/0323559 A1).
Regarding claim 1, Lee et al. (hereafter referred as Lee) teaches an image processing apparatus (Lee, Fig. 8) that executes, on image data, predetermined processing including (i) processing related to detection of the defective pixels (Lee, pre-processor 350, Paragraphs 0097-0099) included in an image sensor used to capture the image data (Lee, Fig. 1, Paragraph 0030), and (ii), processing related to correction of signals of the detected defective pixels (Lee, Paragraphs 0046-0047), comprising one or more processors (Lee, Fig. 8, ISP 300) that execute one or more programs stored in a memory and thereby function as (Lee, Paragraph 0160-0161):
a first processing unit capable of applying the predetermined processing without using any machine learning model (Lee, Fig. 8, DPC1 310 (alternatively, DPC1 310 and pre-processor 350), Paragraph 0046);
a second processing unit capable of applying the predetermined processing using a machine learning model (Lee, Fig. 8, DPC2 320 (alternatively, DPC2 320 and pre-processor 350), Paragraph 0047); and
a control unit configured to control operations of the first processing unit and the second processing unit (Lee, Fig. 8, ISP 300 and/or DP Controller 330, Paragraphs 0083),
wherein the control unit controls whether the predetermined processing is executed by one of the first processing unit and the second processing unit (Lee, Paragraph 0097-0099), or is executed in a shared manner by both the first processing unit and the second processing unit (Lee, Paragraphs 0104-0107, If both types of defective pixels occur, correction is executed in a shared manner.).
Claims 11 and 12 are rejected for the same reasons as claim 1.
Regarding claim 2, Lee teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein
if the predetermined processing is executed in a shared manner by both the first processing unit and the second processing unit, the control unit controls the first processing unit and the second processing unit to execute the processing related to detection and the processing related to correction in a shared manner (Lee, Paragraphs 0104-0107, Correction processing is processing related to the detection.).
Regarding claim 3, Lee teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the control unit controls the first processing unit to execute the processing related to detection (Lee, pre-processor 350, Paragraphs 0097-0099) and the second processing unit to execute the processing related to correction (Lee, Paragraph 0105).
Regarding claim 8, Lee teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the control unit determines whether the second processing unit is to execute the predetermined processing, based on a shooting scene of the image data (Lee, Fig. 12, Step S1230, The second processing unit executes the predetermined processing based on when/if a first image signal is captured (a shooting scene of the image data).) or a shooting mode during capture of the image data.
Regarding claim 10, Lee teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the control unit determines that the second processing unit is to execute the predetermined processing in a case where a temperature of the image processing apparatus is greater than or equal to a threshold (Lee, Fig. 12, Step S1230, The control unit determines the second processing unit is to execute the predetermined processing at Step S1230 regardless of the temperature. Therefore, in a case where a temperature of the image processing apparatus is greater than or equal to an arbitrary threshold, the control unit determines that the second processing unit is to execute the predetermined processing at Step S1230.) or a shutter speed used to capture the image data is longer than or equal to a threshold.
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) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (US 2024/0323559 A1) in view of Iqbal (US 2016/0295113 A1).
Regarding claim 9, Lee teaches the image processing apparatus according to claim 1 (see claim 1 analysis), wherein the control unit determines that the second processing unit is not to execute the predetermined processing (Lee, Paragraph 0097-0099).
However, Lee does not teach wherein the control unit determines that the second processing unit is not to execute the predetermined processing in case where a remaining battery level of the image processing apparatus is less than or equal to a threshold.
In reference to Iqbal, Iqbal teaches a case where a remaining battery level of the image processing apparatus is less than or equal to a threshold (Iqbal, Fig. 2, Step 232, Paragraph 0028-0029).
These arts are analogous since they are both related to imaging devices. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to modify the invention of Lee with the method of reducing resolution of image capture based on battery level as seen in Iqbal to reduce power consumption in a case where a remaining battery level of the image processing apparatus is less than or equal to a threshold. Further, the limitation “wherein the control unit determines that the second processing unit is not to execute the predetermined processing in case where a remaining battery level of the image processing apparatus is less than or equal to a threshold” is met in the scenario in which the control unit determines that the second processing unit is not to execute the predetermined processing and the remaining battery level of the image processing apparatus is less than or equal to a threshold.
Conclusion
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WESLEY JASON CHIU whose telephone number is (571)270-1312. The examiner can normally be reached Mon-Fri: 8am-4pm.
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/WESLEY J CHIU/Examiner, Art Unit 2639
/TWYLER L HASKINS/Supervisory Patent Examiner, Art Unit 2639
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