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 .
Status of Claims
Claims 1-14 are pending.
Response to Arguments
Applicant's arguments filed 02/26/2026 have been fully considered and entered but they are not persuasive.
Firstly, previous objection to title has been withdrawn in view of applicant’s amendment made to the title.
Applicant argues that claims are not a mental process since the invention is designed to automatically generate non-identical images without user operation. Claims require pixel level data manipulation and random movement analysis which cannot be practically performed in human mind, moreover, applicant emphasizes that claims are integrated into a practical application again based on same assertions that automatic generation of images and random mask movements producing a real-world effect. And, lastly applicant states that claims provide improvements since they don’t require manual data collection or user intervention therefore enhancing performance by automation amounting to significantly more.
In reply, examiner disagrees and strongly asserts that first of all limitations such as “to automatically generate non-identical images without user operation” or “pixel level data manipulation” is absolutely missing/non-recited and can not be found in any of the claims that applicant seems to rely upon. In fact, claims do recite receiving a user input.
Secondly, even if claims recite automatic, just by mentioning or reciting the word automatic does not make the claims overcome the abstract idea. There is nothing in claims which prevents from executing it practically in human mind. Moreover, applicant just plainly asserting that claims provide practical application and significantly more based on automatic generation of images, pixel manipulation (which is not even positively recited) is not provided with any concrete evidence to support this assertion.
For example, steps of assessing/acquiring an image is just data gathering or an extra solution activity in the field of endeavor. And steps of partially covering the acquired image with cropping of different areas in the image with randomly changing coverage area to which cropping is applied without going over the edges to then acquire another cropped image out the original image to finally extracting second cropped image from first cropped image based on changed coverage and saving it is an abstract idea, which can be accomplished mentally and/or utilizing generic computer components with mathematical computations. There are no additional elements recited such as use of a particular machine or components other than using generic computer components, even though not recited but if even, they recite the word “automatically generated” which is just an extra solution activity.
Since, all of the limitations in the recited method can be accomplished without reliance on any specific machine or recitation of any additional elements that are sufficient to amount to significantly more (for example, how random movement is significantly more?), therefore, claimed limitations could be accomplished by human minds as there is merely a recitation of generic computing devices such as using generic computer components performing the process. Thus, claims are not patent eligible and previous 101 rejection(s) to claim(s) are repeated below.
Applicant further argues that cited references fail to teach all the limitations of independent claim 1 such as “moving the image mask randomly to change a coverage area of the image mask in the first image, and the coverage area of the image mask does not exceed an edge of the first image; extracting a second image from the first image based on the moved image mask" as recited in claim 1, see remarks, page 8.
In reply, examiner disagrees and asserts that first of all it is a 103 rejection and not a 102 rejection based on just Tazoe as seemed to be argued by the applicant.
For instance, Tazoe only teaches moving the image mask to change a coverage area of the image mask in the first image, and the coverage area of the image mask does not exceed an edge of the first image (mask image is modified and moved according to user’s instructions to change the superimposed coverage area of the mask image over the first image, furthermore, it is made sure by modifications that contour shape of mask image matches and doesn’t exceed over the contour/edge/outline of the first coat image as shown in fig. 12, paragraphs 85, 89) and extracting a second image based on the image mask (selection of at least one mask image from among a plurality of mask images is received from the user and the extraction area defined by the selected mask area in the first image is used as a search key in searching for the second information and the second image similar to the extraction area is determined/extracted, paragraph 154).
Wherein, Kakinuma teaches setting an image mask on the first image, wherein the image mask covers a portion of the image area of the first image and moving (adjusting) image mask to change a coverage area of the image mask in the first image, and the coverage area of the image mask does not exceed an edge of the first image (masking pattern adjustment unit 41 masks parts (i.e., covering portions of image area) of the facial image (i.e., first image) successively, in units of sub-divided area, and increases the masked area (adjusting/moving) while successively moving within the rectangular shaped facial image (i.e., making sure to stay within and not to exceed an edge of first image area), paragraph 63); extracting a second image from the first image based on the moved image mask (note that each time the masking is changed/moved, (second) facial image is extracted from the original facial image area, paragraph 63).
And, Rowlingson was specifically brought in to teach randomly moving image mask to change a coverage area of mask (“composite image 314 is dynamic in that it changes periodically by a portion of the composite image 314 constituting the mask 310 moving randomly in the composite image”, paragraph 47).
As one with ordinary skill can easily see that based not just one reference (i.e., Tazoe) but based on combination of references as shown with Tazoe in view of Kakinuma and Rowlingson successfully teaches all the above argued limitations of claim 1.
In response to applicant's argument that combining teachings of Tazoe with random mask movements teachings of Rowlingson would teach away from the invention by undermining Tazoe’s functionality (the combination of Tazoe with Kakinuma and Rowlingson would not be reasonable to one with ordinary skill to apply random mask movement to Tazoe’s mask), see remarks, page 9, examiner asserts that the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “to automatically generate a plurality of second images from a single first image for use as machine-learning training data”; “intentionally and randomly moves the image mask across different positions of the first image-while ensuring the mask remains within the image boundaries-to extract multiple similar yet slightly different sub-images…random movement of the mask in the present application is not incidental or optional…to maximize data diversity and quantity without manual intervention”, see remarks, page 8, last paragraph) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-14 are directed toward a method and a device which falls within one of the four statutory categories of invention but do not meet the three-prong test for patentability.
Regarding independent claim 1, under step 1, the claim is directed to a method, which is one of the categories of eligible inventions.
Under step 2A Prong 1, the claim recites a system with steps reciting optimizing human activity, specifically, reading/acquiring an image, partially covering/masking/cropping the acquired image with applying masking/crop to different areas of the image without going beyond the overall boundary of the image, thereby acquiring another masked/cropped image out the original image and saving it which is an abstract idea, comprising:
“An image generation method comprising: reading a first image from a storage circuit; setting an image mask on the first image, wherein the image mask covers a portion of the image area of the first image; moving the image mask randomly to change a coverage area of the image mask in the first image, and the coverage area of the image mask does not exceed an edge of the first image; extracting a second image from the first image based on the moved image mask; and storing the second image in the storage circuit”.
It is further noted that steps of assessing/acquiring an image is just data gathering or an extra solution activity in the field of endeavor. And steps of partially covering the acquired image with cropping of different areas in the image with changing coverage area to which cropping is applied without going over the edges to then acquire another cropped image out the original image and finally extracting second cropped image from first cropped image based on changed coverage and saving it is an abstract idea and can all be considered mental processes and can be fully accomplished mentally by manipulating the acquired image while having a pen and paper.
Under step 2A Prong 2, the claim does not recite any additional elements which integrate the judicial exception into a practical application. There are no additional elements recited such as use of a particular machine or components other than using generic computer components.
Moreover, all of the limitations in the recited method can be accomplished without reliance on any specific machine and could be accomplished by human minds and interactions between humans as they are not specifically tailored for execution in any specific machine other than using generic computer components. The claim as a whole does not present a practical application of the abstract idea.
Under Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the abstract idea judicial exception because, as discussed in step 2A, there is merely a recitation of generic computing devices such as using generic computer components performing the process, which are all well-understood routine practices and are purely generic. This finding is consistent with the level of detail of the specification and the well-understood and conventional nature of these elements is broadly covered under court decisions (i) and (iv) from MPEP 2106.05(d)(II) related to receiving and retrieving information in a generic computer environment. The claim is not patent eligible.
Regarding claim 2, it merely adds to claim 1 and further details “wherein the step of setting the image mask on the first image includes: generating the image mask based on a reduction ratio and an original size of the first image”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image to generate cropped image compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 3, it merely adds to claim 2 and further details “wherein the step of setting the image mask on the first image further includes: receiving a user input; and determining the reduction ratio based on the user input”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image to generate cropped image compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 4, it merely adds to claim 1 and further details “wherein the step of randomly moving the image mask includes: determining a movement direction and a movement distance of the image mask randomly; and moving the image mask based on the determined movement direction and movement distance”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image in the random direction and random distance to generate cropped image compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 5, it merely adds to claim 4 and further details “determining a critical value of the movement distance corresponding to a reference direction based on the distance between a first edge of the first image and a first endpoint of the image mask in the reference direction, wherein the first endpoint is closer to the first edge of the first image in the reference direction than the other endpoints of the image mask in the reference direction; and limiting the movement distance of the image mask in the reference direction to not exceed the critical value of the movement distance”. This again only provides a mental process on a generic device with mathematical computation, that can be performed by a human mind with the mere recitation of execution by a generic computing device and communication between generic computing devices which, as in claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 6, it merely adds to claim 1 and further details “wherein the step of randomly moving the image mask comprises: determining a first rotation angle of the image mask randomly; and rotating the image mask based on the first rotation angle”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image to generate cropped image by randomly rotating it compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 7, it merely adds to claim 6 and further details “determining a second rotation angle of the image mask randomly in response to the coverage area of the rotated image mask exceeding the edge of the first image, wherein the first rotation angle is different from the second rotation angle; and re-rotating the image mask based on the second rotation angle”. This again only provides further extra solution activity/data gathering of acquiring an image and performing change in size of the image to generate cropped image by randomly rotating it and re-rotating it without having cropped image go over the edges compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding independent claim 8, under step 1, the claim is directed to an apparatus, which is one of the categories of eligible inventions.
Under step 2A Prong 1, the claim recites a system with steps reciting optimizing human activity, specifically, reading/acquiring an image, partially covering/masking/cropping the acquired image with applying masking/crop to different areas of the image without going beyond the overall boundary of the image, thereby acquiring another masked/cropped image out the original image and saving it which is an abstract idea, comprising:
“An image generation device comprising: a storage circuit; and a processor coupled to the storage circuit, wherein the processor is configured to: reading a first image from the storage circuit; setting an image mask on the first image, wherein the image mask covers a portion of the image area of the first image; moving the image mask randomly to change a coverage area of the image mask in the first image, and the coverage area of the image mask does not exceed an edge of the first image; extracting a second image from the first image based on the moved image mask; and storing the second image in the storage circuit”.
It is further noted that steps of assessing/acquiring an image is just data gathering or an extra solution activity in the field of endeavor. And steps of partially covering the acquired image with cropping of different areas in the image without going over the edges to then acquire another cropped image out the original image and saving it is an abstract idea and can all be considered mental processes and can be fully accomplished mentally by manipulating the acquired image while having a pen and paper.
Under step 2A Prong 2, the claim does not recite any additional elements which integrate the judicial exception into a practical application. There are no additional elements recited such as use of a particular machine or components other than using generic computer components.
Moreover, all of the limitations in the recited method can be accomplished without reliance on any specific machine and could be accomplished by human minds and interactions between humans as they are not specifically tailored for execution in any specific machine other than using generic computer components. The claim as a whole does not present a practical application of the abstract idea.
Under Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the abstract idea judicial exception because, as discussed in step 2A, there is merely a recitation of generic computing devices such as using generic computer components performing the process, which are all well-understood routine practices and are purely generic. This finding is consistent with the level of detail of the specification and the well-understood and conventional nature of these elements is broadly covered under court decisions (i) and (iv) from MPEP 2106.05(d)(II) related to receiving and retrieving information in a generic computer environment. The claim is not patent eligible.
Regarding claim 9, it merely adds to claim 8 and further details “wherein the operation of setting the image mask on the first image by the processor includes: generating the image mask based on a reduction ratio and an original size of the first image”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image to generate cropped image compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 10, it merely adds to claim 9 and further details “wherein the operation of the processor to set the image mask on the first image further comprises: receiving a user input; and determining the reduction ratio based on the user input”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image to generate cropped image compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 11, it merely adds to claim 8 and further details “wherein the operation of the processor to randomly move the image mask comprises: determining a movement direction and a movement distance of the image mask randomly; and moving the image mask based on the movement direction and the movement distance”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image in the random direction and random distance to generate cropped image compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 12, it merely adds to claim 11 and further details “wherein the processor is further configured to: determining a critical value of the movement distance corresponding to a reference direction based on the distance between a first edge of the first image and a first endpoint of the image mask in the reference direction, wherein the first endpoint is closer to the first edge of the first image than the other endpoints of the image mask in the reference direction; and limiting the movement distance of the image mask in the reference direction to not exceed the critical value of the movement distance”. This again only provides a mental process on a generic device with mathematical computation, that can be performed by a human mind with the mere recitation of execution by a generic computing device and communication between generic computing devices which, as in claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 13, it merely adds to claim 8 and further details “wherein the operation of the processor to randomly move the image mask comprises: determining a first rotation angle of the image mask randomly; and rotating the image mask based on the first rotation angle”. This again only provides further extra solution activity of acquiring an image and performing change in size of the image to generate cropped image by randomly rotating it compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
Regarding claim 14, it merely adds to claim 13 and further details “wherein the operation of the processor to randomly move the image mask further comprises: determining a second rotation angle of the image mask randomly in response to the coverage area of the rotated image mask exceeding the edge of the first image, wherein the first rotation angle is different from the second rotation angle; and re-rotating the image mask based on the second rotation angle”. This again only provides further extra solution activity/data gathering of acquiring an image and performing change in size of the image to generate cropped image by randomly rotating it and re-rotating it without having cropped image go over the edges compared to originally acquired image which is a mental process on a generic device, that could be performed unaided by a human, recited as performed by a generic computing device, and thus, as in the claim do not constitute practical application or significantly more than the abstract idea.
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 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 1-3 and 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Tazoe et al., US 2015/0269189 in view of Kakinuma et al., US 2007/0127788 further in view of Rowlingson, US 2017/0011212.
Regarding claim 8, Tazoe discloses an image generation device (apparatus 10, fig. 1, paragraph 25) comprising: a storage circuit (memory 14, paragraph 25) ; and a processor coupled to the storage circuit (controller 12 coupled to memory 14 as shown in fig. 1, paragraph 25), wherein the processor is configured to:
reading a first image from the storage circuit (obtaining device 26 of apparatus 10 can read, from the memory 14, a first image that has been stored in advance, paragraph 71); setting an image mask on the first image, wherein the image mask covers a portion of the image area of the first image (user selects a single mask image 50 and controller performs control to display the selected mask image 50 by superimposing it on the obtained first image by only covering portion of it, as shown in fig. 11(C), paragraphs 81-84);
moving the image mask to change a coverage area of the image mask in the first image, and the coverage area of the image mask does not exceed an edge of the first image (mask image is modified and moved according to user’s instructions to change the superimposed coverage area of the mask image over the first image, furthermore, it is made sure by modifications that contour shape of mask image matches and doesn’t exceed over the contour/edge/outline of the first coat image as shown in fig. 12, paragraphs 85, 89);
extracting a second image based on the image mask (selection of at least one mask image from among a plurality of mask images is received from the user and the extraction area defined by the selected mask area in the first image is used as a search key in searching for the second information and the second image similar to the extraction area is determined/extracted, paragraph 154);
and storing the second image in the storage circuit (the extracted second images in the second information are registered and the second information in the memory 14 is updated, paragraph 122).
Tazoe fails to explicitly disclose moving image mask randomly to change a coverage area of image mask; extracting a second image from first image based on moved image mask.
However, Kakinuma teaches setting an image mask on the first image, wherein the image mask covers a portion of the image area of the first image and moving (adjusting) image mask to change a coverage area of the image mask in the first image, and the coverage area of the image mask does not exceed an edge of the first image (masking pattern adjustment unit 41 masks parts (i.e., covering portions of image area) of the facial image (i.e., first image) successively, in units of sub-divided area, and increases the masked area (adjusting/moving) while successively moving within the rectangular shaped facial image (i.e., making sure to stay within and not to exceed an edge of first image area), paragraph 63); extracting a second image from the first image based on the moved image mask (note that each time the masking is changed/moved, (second) facial image is extracted from the original facial image area, paragraph 63).
Tazoe and Kakinuma are combinable because they both are in the same field of endeavor dealing with masking of image data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to combine the teachings of Tazoe with the teachings of Kakinuma for the benefit of accurately recognizing the images, in particular effectively masking facial images contained in posters or sign boards or similar, and eliminating unnecessary facial image recognition processing as taught by Kakinuma at paragraph 8.
Tazoe with Kakinuma fails to explicitly teach moving image mask randomly to change a coverage area of image mask.
However, Rowlingson teaches moving image mask randomly to change a coverage area of image mask (“composite image 314 is dynamic in that it changes periodically by a portion of the composite image 314 constituting the mask 310 moving randomly in the composite image”, paragraph 47).
Tazoe and Kakinuma are combinable with Rowlingson because they all are in the same field of endeavor dealing with masking of image data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to combine the teachings of Tazoe and Kakinuma with the teachings of Rowlingson for the benefit of having both the mask and the user challenge to be moved randomly in order to prevent a software agent from identifying aspects of the composite image that never change as candidate aspects for the determination of the user challenge as taught by Rowlingson at paragraph 13.
Regarding claim 9, Tazoe further discloses wherein the operation of setting the image mask on the first image by the processor includes: generating the image mask based on a reduction ratio and an original size of the first image (mask image is superimposed on to the first image based on the amount of enlargement or reduction of aspect ratio of the selected mask image, for example, user instructs modification in the change of size and aspect ratio of the mask image in order to match with the shape/size of the original first coat image, paragraphs 85, 89).
Regarding claim 10, Tazoe further discloses wherein the operation of the processor to set the image mask on the first image further comprises: receiving a user input; and determining the reduction ratio based on the user input (image mask modification changes are inputted by user and mask image is changed based on inputted changes, for example, user instructs modification in the change of size and aspect ratio of the mask image in order to match with the shape/size of the original first coat image, paragraphs 85, 89).
Regarding claim 1, is a method version of claim 8 reciting similar features, and thus, is rejected on the same rationale.
Regarding claim 2, is a method version of claim 9 reciting similar features, and thus, is rejected on the same rationale.
Regarding claim 3, is a method version of claim 10 reciting similar features, and thus, is rejected on the same rationale.
Claims 4 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Tazoe et al., US 2015/0269189 in view of Kakinuma et al., US 2007/0127788 further in view of Rowlingson, US 2017/0011212 as applied in claim 8 above and further in view of Shin et al., US 2020/0124980.
Regarding claim 11, Combination of Tazoe with Kakinuma and Rowlingson further teaches wherein the operation of the processor to randomly move the image mask comprises: determining a movement direction of the image mask randomly (Rowlingson, “the random movement of the mask 310 component of the dynamic composite image 314 is realized by the mask 310 moving in the composite image 314 in a random direction independently determined for each period. Thus, in this way, the mask 310 can move as a whole in random directions after each interval”, paragraph 53); and moving the image mask based on the movement direction (Tazoe, determining direction of selected mask and rotates the mask image 50C in determined direction, paragraphs 85, 94 and Rowlingson, the mask 310 can move as a whole in random directions, paragraph 53).
Tazoe and Kakinuma are combinable with Rowlingson because they all are in the same field of endeavor dealing with masking of image data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to combine the teachings of Tazoe and Kakinuma with the teachings of Rowlingson for the benefit of having both the mask and the user challenge to be moved randomly in order to prevent a software agent from identifying aspects of the composite image that never change as candidate aspects for the determination of the user challenge as taught by Rowlingson at paragraph 13.
Combination of Tazoe with Kakinuma and Rowlingson fails to further teach determining a movement distance of image mask randomly and moving the image mask based on movement distance.
However, Shin teaches determining a movement distance of image mask randomly and moving the image mask based on movement distance (first, second, third, and fourth sides of the mask may be modified by different distances, which are randomly determined and applied, paragraph 51).
Tazoe, Kakinuma and Rowlingson are combinable with Shin because they all are in the same field of endeavor dealing with image processing and masking of image data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to combine the teachings of Tazoe, Kakinuma and Rowlingson with the teachings of Shin for the benefit of arbitrarily modifying a mask a plurality of times to extract an optimally adjusted value to minimize errors in the case of an application to an actual image processing process as taught by Shin at paragraph 66.
Regarding claim 4, is a method version of claim 11 reciting similar features, and thus, is rejected on the same rationale.
Claims 6 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Tazoe et al., US 2015/0269189 in view of Kakinuma et al., US 2007/0127788 further in view of Rowlingson, US 2017/0011212 as applied in claim 8 above and further in view of Milam et al., US 2025/0069387.
Regarding claim 13, Tazoe further discloses determining a first rotation angle of the image mask and rotating the image mask based on the first rotation angle (Tazoe, direction of rotation of the mask image is expressed using the direction and amount of rotation around the X-axis and using the direction and amount of rotation around the Y-axis (i.e., rotation angle) and the axis of rotation, the direction of rotation, and the amount of rotation are specified and image mask is thereby rotated as per the user operation, paragraphs 86, 94-95).
Combination of Tazoe with Kakinuma and Rowlingson fails to further teach determining a rotation angle of mask randomly.
However, Milam teaches determining a first rotation angle of image mask randomly and rotating the image mask based on the first rotation angle (positional augmentations are performed on the respective masks such as image masks are rotated at a randomly selected degree of multiples of 90 degrees, paragraph 51).
Tazoe, Kakinuma and Rowlingson are combinable with Milam because they all are in the same field of endeavor dealing with image processing and masking of image data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to combine the teachings of Tazoe, Kakinuma and Rowlingson with the teachings of Milam for the benefit of automating the process by randomly applying various automated settings to achieve favorable results as taught by Milam at abstract and paragraph 51.
Regarding claim 6, is a method version of claim 13 reciting similar features, and thus, is rejected on the same rationale.
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Tazoe et al., US 2015/0269189 in view of Kakinuma et al., US 2007/0127788 further in view of Rowlingson, US 2017/0011212 further in view of Milam et al., US 2025/0069387 as applied in claim 13 above and further in view of Nishibe, US 2012/0050279.
Regarding claim 14, Tazoe further discloses determining a rotation angle of the image mask in response to the coverage area of the rotated image mask exceeding the edge of the first image and re-rotating the image mask based on the rotation angle (Tazoe, rotation of the mask image is expressed using amount of rotation around the X-Y axis (i.e., rotation angle) and this axis of rotation including aspect ratio of mask image is superimposed on to the first image based on user specifications, however, in a case where contour/edge/outline of selected mask image doesn’t match with original image (i.e., exceeds over), then user instructs modification in the change of axis of rotation (i.e., rotation angle), the direction of rotation, and the amount/aspect ratio of rotation of the mask image to thereby further modify (re-rotate) the mask image as per the user operation in order to match it with the shape/size of the original first coat image as shown in fig. 12, paragraphs 86, 89, 94-95).
Combination of Tazoe with Kakinuma, Rowlingson fails to further teach determining a second rotation angle of the image mask randomly in response to exceeding edge of image, wherein first rotation angle is different from the second rotation angle; and re-rotating the image based on the second rotation angle.
However, Milam teaches determining a rotation angle of image mask randomly and rotating the image mask based on the rotation angle (positional augmentations are performed on the respective masks such as image masks are rotated at a randomly selected degree of multiples of 90 degrees, paragraph 51).
Tazoe, Kakinuma and Rowlingson are combinable with Milam because they all are in the same field of endeavor dealing with image processing and masking of image data.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to combine the teachings of Tazoe, Kakinuma and Rowlingson with the teachings of Milam for the benefit of automating the process by randomly applying various automated settings to achieve favorable results as taught by Milam at abstract and paragraph 51.
Combination of Tazoe with Kakinuma, Rowlingson and Milam fails to further teach determining a second rotation angle of image in response to exceeding edge of image, wherein first rotation angle is different from the second rotation angle; and re-rotating the image based on the second rotation angle.
However, Nishibe teaches determining a second rotation angle of image in response to exceeding edge of image (when rotation angle, theta1 (i.e., first rotation angle) increases to an angle slightly exceeding an angle which is a boundary of a range and then decreases to below this angle, theta2 (i.e., second rotation angle) which is within the boundary range, paragraph 80), wherein first rotation angle is different from the second rotation angle (first and second rotation theta angles are different, paragraph 80); and re-rotating the image based on the second rotation angle (image is rotated according to second theta angle to be within the boundary range, paragraph 80).
Tazoe, Kakinuma, Rowlingson and Milam are combinable with Nishibe because they all are in the same field of endeavor dealing with applying various image processing techniques.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to combine the teachings of Tazoe, Kakinuma, Rowlingson and Milam with the teachings of Nishibe for the benefit of providing i novel and improved image processing techniques which are capable of reducing the influence to parallax caused due to a change in display of a stereoscopic image as taught by Nishibe at paragraph 5.
Regarding claim 7, is a method version of claim 14 reciting similar features, and thus, is rejected on the same rationale.
Allowable Subject Matter
Claims 5 and 12 are objected to as being dependent upon a rejected base claim, but would be allowable if 101 rejections as set forth in this action are overcome and are rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: cited prior arts and other related prior arts do not expressly teach all the limitations of claim 12 such as: “wherein the processor is further configured to: determining a critical value of the movement distance corresponding to a reference direction based on the distance between a first edge of the first image and a first endpoint of the image mask in the reference direction, wherein the first endpoint is closer to the first edge of the first image than the other endpoints of the image mask in the reference direction; and limiting the movement distance of the image mask in the reference direction to not exceed the critical value of the movement distance”.
Claim 5 is a method version of claim 12 reciting similar features.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Watanabe, US 2012/0014608
Ahn et al., US 2011/0221932
Hasegawa, US 2008/0240598
Masuda, US 2008/0193018
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/PAWAN DHINGRA/Examiner, Art Unit 2683
/ABDERRAHIM MEROUAN/Supervisory Patent Examiner, Art Unit 2683