DETAILED ACTION
The action is in response to the original filing on February 13, 2024, and the Remarks and Amendments filed on July 30, 2026. Claims 1-6, 9-18 & 20 are pending and have been considered below. Claims 1, 13, & 20 have been amended. Claims 7, 8, & 19 are cancelled.
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
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 6, 8-13, & 20 are rejected under 35 U.S.C. 103 as being unpatentable over Krissy’s Krazy Fun Channel (“Chuck E Cheese Sketch Book Arcade Drawing Game ~ Draw Sketch Your Picture Game”) (herein after “Krissy”) in view of Jia-Bin Huang (U.S. Pat. App. Pub. No. CN 110288519 A, herein after “Huang”) and further in view of Dmitry Sytnik Et. Al. (US 20210150676 A1, herein after “Sytnik”).
Regarding claims 1, 13 & 20, Krissy discloses a method for processing media content (“Chuck E Cheese Sketch Book Arcade Drawing Game ~ Draw Sketch Your Picture Game), comprising: displaying video media content in a display interface (Timestamp :01-1:00),
the video media content comprising at least one target video (Timestamp :24)
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frame with a target object (Timestamp :15);
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The frame at timestamp :15 seconds shows a “Chuck E Cheese” arcade machine displaying an image with a target object, a child with a doll. Further, a later frame at timestamp :23 seconds shows that the image is a frame in a video of the baby with the doll.
generating a drawn image associated with the target object… (Timestamp 1:01)
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and switching to display, in the display interface, a preset virtual brush and a drawing process of the drawn image by the virtual brush (Timestamp :25-:34).
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The drawn image appears gradually starting at timestamp :29 seconds in Krissy’s uploaded video, and the complete product can be viewed on screen and printed as seen in timestamp 1:00 minute.
dynamically displaying, on the drawn image, a drawing process of the target decoration masking by the virtual brush (Krissy, timestamp :29) Krissy teaches a method of dynamically displaying a drawing process of an image by use of a virtual brush.
Krissy fails to expressly disclose that in response to that the target video frame satisfies a preset drawing condition, and generation of the drawn image associated with the target object is based on contour information of the target object in the target video frame
determining a decoration masking to be processed;
performing an adjustment operation on the decoration masking to be processed based on the drawn image to obtain a target decoration masking,
wherein determining the decoration masking to be processed comprises:
in response to a decoration operation, displaying at least one preset decoration masking; and
in response to a selection operation on the at least one preset decoration masking, determining a selected decoration masking as the decoration masking to be processed.
Huang teaches generation of the drawn image associated with the target object is based on contour information of the target object in the target video frame (“… the body contour region to perform deformation operation to obtain the human body outline deformation image”; Huang, page 10.) where a contour region is found and modified to produce an output deformation image, and (“… the key point set based on the edge, determining the body contour of the target object, comprising: obtaining the edge key point of each partial matching frame after the key point set, using the connecting method of the Hermite interpolation, connected to the respective edge of the key point, generating an object body contour.”; Huang, page 3).
wherein the preset drawing condition comprises at least one of: a target key point existing in the target video frame “the target object in the target image is executing key point detection, to obtain human body key points on the target image of the target object” (Huang, Page 2), the target object in the target video frame making a target action, or the target object in the target video frame making a target expression “the target image formed, can aim at the head area and human body area key point detection, so as to obtain the plurality of head region key point and a plurality of human body area key point. key point detection of the head area and human body area can adopt such as CPM (Convolutional Pose Machine, convolution gesture detector)” (Huang, Page 6) where a convolution gesture detector is known in the art to recognize expressions or actions.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of obtaining a target video frame with target object, and display interface with virtual brush for drawing process of the target object taught by Krissy, with the teachings of Huang to include key point detection. The motivation to do so would be to recognize the target object with contour detection.
Krissy and Huang fail to teach in response to that the target video frame satisfies a preset drawing condition
determining a decoration masking to be processed;
performing an adjustment operation on the decoration masking to be processed based on the drawn image to obtain a target decoration masking; and
wherein determining the decoration masking to be processed comprises:
in response to a decoration operation, displaying at least one preset decoration masking; and
in response to a selection operation on the at least one preset decoration masking, determining a selected decoration masking as the decoration masking to be processed.
Sytnik teaches in response to that the target video frame satisfies a preset drawing condition “The exemplary systems can be used to detect and identify the types of objects in an image, and adjust local contrast of the objects using various techniques based on the type of object identified in the image” (Sytnik, ¶ [0047]) where detecting an object satisfies the condition for editing.
determining a decoration masking to be processed “the mask generation module 130 can determine that out-of-focus areas are not included or detected in the image 170” (Sytnik, ¶ [0060]) determines where to mask, and “The mask generation module 130 and the neural network 118 thereby receive as input the image 170 and generate the segmented mask 190 for each pixel of the image 170 in which people, the sky and water are detected. As an example, a probability value can be used for determining the probability of the pixel being associated with people, the sky and water” (Sytnik, ¶ [0071]) determines what to mask;
performing an adjustment operation on the decoration masking to be processed based on the drawn image to obtain a target decoration masking “The structure booster module 136 can apply a guided filter with the appropriate parameters for the in-focus area 312 and the out-of-focus area 310 in the original image 170. The parameters can be applied with greater strength (e.g., a higher value) for the in-focus area 312, and can be avoided for the out-of-focus area 310 to avoid over-sharpening of the out-of-focus area 310” (Sytnik, ¶ [0074]) where different modules are used to adjust the image based on desired properties.
wherein determining the decoration masking to be processed comprises:
in response to a decoration operation, displaying at least one preset decoration masking “The user interface 114 includes an adjustment section 324 including multiple controls in the form of, e.g., sliders, check boxes, input boxes, preset enhancements, combinations thereof, or the like, for various setting controls associated with the image in the image section 322” (Sytnik, ¶ [0080]) where preset enhancements can be selected within the user interface. The enhancements may be color correcting, filtering, or shading effects ¶ [0077]-[0079] which are read as decorating the masked area under the claim’s broadest reasonable interpretation ; and
in response to a selection operation on the at least one preset decoration masking, determining a selected decoration masking as the decoration masking to be processed “FIG. 25 is a screenshot illustrating a user interface 114 of the system 100 in accordance with the present disclosure. The user interface 114 includes an image selection section 320 including multiple imported images for potential editing” (Sytnik, ¶ [0080]) where a selection section is utilized for the user to pick an enhancement, additionally “The adjustment section 324 includes an on/off switch 326 for turning all structure enhancements on and off. The adjustment section 324 includes a slider selector 328 for gradual selection of the amount of the super clarity enhancements and a slider selector 330 for gradual selection of the amount of the structure booster enhancements” (Sytnik, ¶ [0082]).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the methods taught by Krissy and Huang, with the teachings of Sytnik to include a method of determining image masking and performing adjustment operations on the decoration masking. The suggestion/motivation to do so would have been to provide user entertainment, image enhancement, and to allow for beautification methods to be applied as noted by Krissy, Sytnik, and Huang. Implementing the methods taught by Huang to determine key points of a target object to establish a contour line, with Sytnik to utilize a decoration masking, and with Krissy to display an image and draw the target image would yield the predictable result of a drawn target image based on contour information.
In regard to claim 13, claim 1 is substantially similar to claim 13 hence the rejection analysis for claim 1 is also applied to claim 13. Krissy also teaches the additional limitations of claim 13 which recites an electronic device, comprising: a processor and a memory; the memory storing computer execution instructions; and the processor executing the computer execution instructions stored in the memory, to cause the processor to perform acts comprising (Timestamp between :00-1:00).
In regard to claim 20, claim 1 is substantially similar to claim 20 hence the rejection analysis for claim 1 is also applied to claim 20. Krissy also teaches the additional limitations of claim 20 which recites a non-transitory computer readable storage medium storing computer execution instructions, the computer execution instructions, when executed by a processor, implementing acts comprising… the video from Krissy between :00-1:00 teaches an arcade machine, which includes a non-transitory computer readable storage medium storing computer execution instructions.
Regarding claims 2 & 14, Krissy in view of Huang and Sytnik teaches that in response to that the target video frame satisfies the preset drawing condition, generating the drawn image associated with the target object based on the contour information of the target object in the target video frame comprises: (Krissy, timestamp :01-1:00 & Huang, page 10)
performing a recognition operation on the target object in the target video frame to obtain a recognition result(“based on the human body key point, determining the target object of the first centre point and the second centre point; based on the first centre point and the second centre point, determining the target object body centre line.”; Huang, page 2, where the method of determining a target object is known to be a recognition operation that finds a target object based on key points, where “the key point set based on the edge, determining the body contour of the target object.” (Huang, page 3));
determining whether the target object satisfies the preset drawing condition based on the recognition result (“calculating the output probability of the combined to the edge critical point between the skeleton key set, the candidate key point edge key point probability of the output is 1 of the key candidate edge point is determined to be the skeleton key point matching, the output probability is 0 determined as the edge key point of the skeleton key point does not match”; Huang, page 3); and
in response to that the target object satisfies the preset drawing condition, generating the drawn image associated with the target object based on the contour information of the target object(“… According to a particular implementation of the present disclosure, the key point set based on the edge, determining the body contour of the target object, comprising: obtaining the edge key point of each partial matching frame after the key point set, using the connecting method of the Hermite interpolation, connected to the respective edge of the key point, generating an object body contour.”; Huang, page 3).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the methods of drawing a target object taught by Krissy with the method of a recognition operation used for a recognition result that checks for compliance with a preset drawing condition taught by Huang to produce a drawing operation capable of recognizing the target object based on contour information. The suggestion/motivation to do so would have been to make a photo more refined and provide emphasis on a specific aspect of a photo, where “the embodiment of the present disclosure provides an image beautification method … on the target image of the human body key point, based on the human body key point, determining body contour and head protection region.” (Huang, page 3).
In regard to claim 14, claim 2 is substantially similar to claim 14 hence the rejection analysis for claim 2 is also applied to claim 14. Krissy also teaches the additional limitations of claim 14 which recites the device of claim 13… the video from Krissy between :00-1:00 teaches an arcade machine, which includes an electronic device, comprising: a processor and a memory; the memory storing computer execution instructions; and the processor executing the computer execution instructions stored in the memory, to cause the processor to perform acts comprising.
Regarding claims 6 & 18, Krissy in view of Huang and Sytnik teaches of switching to display, in the display interface, the preset virtual brush and the drawing process of the drawn image by the virtual brush comprises: (Krissy, timestamp :01-1:00)
displaying, in a first display area of the display interface, the preset virtual brush and the drawing process of the drawn image by the virtual brush (Krissy, timestamp :01-1:00) it can be seen in the video that a girl with a doll are pictured in a first display, and after their photo is taken, a virtual brush draws them both; and
displaying, in a second display area of the display interface, the target object in the video media content (Krissy, timestamp :00) there is a second display on the lower portion arcade machine for outputting instructions and the live video, including the target object.
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In regard to claim 18, claim 6 is substantially similar to claim 18 hence the rejection analysis for claim 6 is also applied to claim 18. Krissy also teaches the additional limitations of claim 18 which recites the device of claim 13… the video from Krissy between :00-1:00 teaches an arcade machine, which includes an electronic device, comprising: a processor and a memory; the memory storing computer execution instructions; and the processor executing the computer execution instructions stored in the memory, to cause the processor to perform acts comprising.
Regarding claim 9, Krissy in view of Huang and Sytnik teach the method of claim 1,
wherein performing the adjustment operation on the decoration masking to be processed based on the drawn image to obtain the target decoration masking comprises: (Huang, page 6)
determining position information of at least one key point corresponding to the target object (“after obtaining the human body centre line, … based on the body center line of body contour for deformation operation. specifically, the body center line the body contour is divided into left and right two parts, can be compression deformation towards the centre line direction through the left and right parts.” (Huang, page 7)); and
performing a size scaling operation and/or a shape adjustment operation on the decoration masking to be processed based on the position information of the at least one key point, to obtain the target decoration masking (“based on the human body key point, determining the human body outline and head protection region … performed on the human body outline area deformation operation to obtain the human body outline deformation image.” (Huang, page 4)) where the key points are used to determine the body outline for accurate target image deformation/beautification.
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Regarding claim 10, Krissy in view of Huang and Sytnik teach the method of claim 9,
wherein dynamically displaying on the drawn image the drawing process of the target decoration masking by the virtual brush comprises: (Krissy, timestamp :01-1:00 & Huang, page 6)
determining a display position of the target decoration masking on the drawn image according to the position information of the at least one key point (“based on the first centre point and the second centre point, determining the target object body centre line” (Huang, page 7)) where key points are used to determine the position and location of the target object within the target image, and the beautification methods are applied within the contour of the key points; and
dynamically displaying the drawing process of the target decoration masking by the virtual brush on the drawn image based on the display position (Krissy, timestamp :29) Krissy teaches a method of dynamically displaying a drawing process of an image by use of a virtual brush.
Regarding claim 11, Krissy in view of Huang and Sytnik teach the method of claim 1,
wherein the decoration masking comprises a human face processing masking and/or a human body processing masking (“the target object in the target image is executing key point detection so as to obtain the target object on the human body key point of the target image.” (Huang, page 5)) it is noted that using key points to detect portions of the human body also apply to the head and face, beautification masking can be done through these key points and their locations, therefore, Huang teaches beautification masking for the body and/or face.
Regarding claim 12, Krissy in view of Huang and Sytnik teach the method of claim 1,
further comprising:
in response to a generation operation triggered by a user, generating target media content based on the drawing process corresponding to the drawn image and/or the drawing process of the target decoration masking (“communication device 509 may allow electronic device 50 with other device for wireless or wired communication to exchange data.” (Huang, page 11)) Huang notes an I/O interface may allow communication of data such as uploading or downloading. Additionally, Krissy at timestamp 1:00 minute shows the output of the drawing containing a print feature, and at timestamp :01 seconds, a generation operation must be selected by the user.
Claim(s) 3-5 & 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Krissy, Huang, Sytnik, and further in view of Tong Li et. al. (U.S. Pat. App. Pub. No. US 20210035260 A1, herein after “Tong”).
Regarding claims 3 & 15, Krissy in view of Huang and Sytnik teaches the method of claim 2,
in response to determining, according to the recognition result, that an expression feature of the target object matches a preset target expression and/or an action feature of the target object matches a preset target action, determining that the target object satisfies the preset drawing condition(“After the target image formed, can aim at the head area and human body area key point detection, so as to obtain the plurality of head region key point and a plurality of human body area key point. key point detection of the head area and human body area can adopt such as CPM (Convolutional Pose Machine, convolution gesture detector)”; Huang, page 6) where it is known that a convolutional pose machine (CPM) is a sequence of networks that map a location of identified parts such as fingers on a hand, or ligaments on a body.
Krissy, Sytnik, and Huang do not teach wherein determining whether the target object satisfies the preset drawing condition based on the recognition result comprises at least one of:
in response to determining, according to the recognition result, that the target object comprises a preset target key point, determining that the target object satisfies the preset drawing condition.
Tong teaches wherein determining whether the target object satisfies the preset drawing condition based on the recognition result comprises at least one of:
in response to determining, according to the recognition result, that the target object comprises a preset target key point, determining that the target object satisfies the preset drawing condition (“… a detection unit and a deformation processing unit, where the detection unit is configured to obtain a first image, identify a target object in the first image, and obtain leg detection information of the target object”; Tong, ¶ [0007]) where the key point information is based on a target line which may also be referred to as a center line, and the resulting contour lines may be used to modify the image.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the methods of target points observed on a target object, used to determine a preset condition taught by Tong, with the teachings of Huang to produce a recognition function that can observe and identify target expressions or actions. The suggestion/motivation to do so would have been to allow for more accurate, and on-demand image processing. “…to implement automatic adjustment … of the target object without multiple manual operations of a user, which greatly improves operational experiences of the user.” (Tong, ¶ [0072]).
In regard to claim 15, claim 3 is substantially similar to claim 15 hence the rejection analysis for claim 3 is also applied to claim 15. Krissy also teaches the additional limitations of claim 15 which recites the device of claim 13… the video from Krissy between :00-1:00 teaches an arcade machine, which includes an electronic device, comprising: a processor and a memory; the memory storing computer execution instructions; and the processor executing the computer execution instructions stored in the memory, to cause the processor to perform acts comprising.
Regarding claims 4 & 16, Krissy in view of Huang and Sytnik teaches the method of claim 3,
performing a drawing operation on the contour information by a preset target brush, to obtain a first drawing result (Huang, page 3 and Krissy, Timestamp :29-1:01) where in this portion of the video, a virtual brush is drawing the target object to produce a drawing result.
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Krissy, Sytnik, and Huang do not teach wherein generating the drawn image associated with the target object based on the contour information of the target object comprises:
recognizing contour information corresponding to the target object, wherein the contour information comprises outer contour information and inner contour information;
determining a hair region contour corresponding to the target object by using a preset hair segmentation algorithm, and
obtaining a second drawing result based on the hair region contour.
Tong teaches wherein generating the drawn image associated with the target object based on the contour information of the target object comprises:
recognizing contour information corresponding to the target object, wherein the contour information comprises outer contour information and inner contour information (“It may be understood that the leg region of the target object has an inner contour and an outer contour, that is, the leg region may have an outer contour line and an inner contour line. “(Tong, ¶ [0025]));
determining a hair region contour corresponding to the target object by using a preset hair segmentation algorithm, and obtaining a second drawing result based on the hair region contour (“the plurality of sub-regions include a first sub-region and a second sub-region. The first sub-region and the second sub-region correspond to a thigh region of the leg region.” (Tong, ̬¶ [0043])) where the preset sub-regions can be designated to an adjacent part of the human body;
obtaining the drawn image associated with the target object based on the first drawing result and the second drawing result (“… the plurality of sub-regions include a first sub-region and a second sub-region. The first sub-region and the second sub-region correspond to a thigh region of the leg region.” (Tong, ¶ [0082])) where there may be multiple sub-regions of adjacent body parts, and the final image is obtained through the combination of multiple sub-regions.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the methods of drawing a target object with contour information by a target brush by Krissy, Sytnik, and Huang with the teachings of Tong to perform a second contour recognition, and combine the two to produce the drawn image. The suggestion/motivation to do so would have been to identify multiple key points for later modifications. “… performing compression processing … or performing stretching processing … according to a direction from the target line to the contour line.” (Tong, ¶ [0027]).
In regard to claim 16, claim 4 is substantially similar to claim 16 hence the rejection analysis for claim 4 is also applied to claim 16. Krissy also teaches the additional limitations of claim 16 which recites the device of claim 13… the video from Krissy between :00-1:00 teaches an arcade machine, which includes an electronic device, comprising: a processor and a memory; the memory storing computer execution instructions; and the processor executing the computer execution instructions stored in the memory, to cause the processor to perform acts comprising.
Regarding claims 5 & 17, Krissy in view of Sytnik, Huang, and Tong teach the method of claim 4,
wherein determining the hair region contour corresponding to the target object by using the preset hair segmentation algorithm comprises: (Tong, ¶ [0043])
performing a segmentation operation on the target object by the preset hair segmentation algorithm, to obtain a target mask corresponding to the hair region (“outline the region … of the key point comprises, eyes, nose and ear organs such as the key point set,” (Huang, page 9)) where the outline has an output probability based on the edge critical point, the output probability determines what portion of the human body will be displayed, therefore segmenting it for modifications, (“After determining a graphic for the head region, according to the head area enlarging coefficient, in a head area pattern is central, outwards expanding pattern area, obtaining the head protection area.” (Huang, page 9)) where a head protection area is separate from the human body outline, it is understood that the values to determine a protection area could be altered for another part of the human body, such as the hair.
Determining the second drawing result corresponding to the target object according to a preset channel value range and the target mask (“… the candidate key point edge key point probability of the output is 1 of the key candidate edge point is determined to be the skeleton key point matching, the output probability is 0 determined as the edge key point of the skeleton key point does not match” (Huang, page 3)) where 0 to 1 is a preset channel value range, the candidate edge is tested to match the skeleton key set, and the process can be repeated for multiple portions of the human body for a plurality of image results.
In regard to claim 17, claim 5 is substantially similar to claim 17 hence the rejection analysis for claim 5 is also applied to claim 17. Krissy also teaches the additional limitations of claim 17 which recites the device of claim 13… the video from Krissy between :00-1:00 teaches an arcade machine, which includes an electronic device, comprising: a processor and a memory; the memory storing computer execution instructions; and the processor executing the computer execution instructions stored in the memory, to cause the processor to perform acts comprising.
Response to Arguments
Applicant's arguments filed July 30th, 2026, have been fully considered but they are not persuasive.
Applicant argues on page 14 of the Remarks that Sytnik fails to teach determining a decoration masking to be processed because of the temporal limitation that the determining step must occur after a switch to display and drawing process. Sytnik discloses a method of decoration masking applied to an input original image “With reference to FIG. 6, the mask generation module 130 can receive as input the original image 170, and is executed by the processing device 108 to generate a person mask 174” ¶ [0059] and “The system 100 further applies different enhancement strengths for different zones in focus and out-of-focus in the image 170 based on the segmented mask 190” ¶ [0072]. Since no specific method of masking or further limiting filter is claimed in the limitation, the masking reads upon the current claim language. Sytnik does not disclose a first switch to display or drawing process, however, when applied in combination with the Krissy reference, the displayed drawn image could serve as an input image for the Sytnik reference to determine decoration masking.
Applicant further argues on pages 15-16 of the Remarks that Sytnik fails to teach dynamically displaying, on the drawn image, a drawing process of the target decoration masking by the virtual brush. Sytnik does not teach of a virtual brush or dynamic drawing process, but when in combination of Krissy, the claimed limitation is taught. Krissy utilizes a drawing process with a virtual brush, but does not teach of decoration masking. Applicant states that the decoration masking is a visible overlay applied on the drawn image to produce effects such as beautification. Sytnik does teach of filters, applied on an image, which are intended to improve the visual appeal of the image which is read as beautification. Sytnik does teach of determining a masking area ¶ [0072] and adjusting the parameter strength ¶ [0074]. The Examiner cannot confidently affirm that the current claim language is considered novel in view of the prior art because no specific method of producing the beautification or decoration masking is claimed while not taught by the combination of cited references.
Applicant further argues on pages 16-17 of the Remarks that no cited reference teaches the amended claim limitations. An updated rejection is provided above in view of the amended claims. Sytnik teaches of a triggered decoration process ¶ [0082]-[0084] where the user may select an enhancement to apply to the image. Sytnik’s methods of mask generation may be automatic, or selected/edited by a user.
Applicant further argues that Sytnik has a fundamentally different domain from the Krissy reference since Krissy utilizes a video media to detect objects in video frames and Sytnik relates to static image enhancement. Examiner would like to note the Krissy reference is capable of drawing a frame, or static image which may then be input as an original image to obtain the product achieved by the Sytnik reference’s enhancements. In response to Applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the Examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, the static image, or frame produced by Krissy may be input as the original image in Sytnik to yield a predictable result of an enhanced drawn image where the motivation would be a desire for the effects produced by Sytnik on an image produced by Krissy.
Applicant additionally notes on pages 17-18 of the Remarks that the combined references would not achieve the claimed invention due to missing features. Applicant states that a person of ordinary skill would not achieve a system that determines a user-selectable decoration masking, adjusts it based on a drawn image, and dynamically displays a drawing process of the decoration masking by a virtual brush on the drawn image. The Examiner believes that the prior art is capable of teaching these limitations in combination by utilizing the image enhancements from Sytnik in combination with a drawn image from a frame and the drawing process using a virtual brush provided by Krissy, see MPEP 2141 KSR rationale C. Use of known technique to improve similar devices (methods, or products) in the same way.
Conclusion
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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/C.A.U./Examiner, Art Unit 2611
/TAMMY GODDARD/Supervisory Patent Examiner, Art Unit 2611
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