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 .
Specification
The clean copy and the marked-up copies of the specifications filed on 09/25/2024 are entered and made of record.
Claims
Claims 1-7, 10-11 and 13-23 are examined by the examiner. Claims 8-9 and 12 were cancelled by the amendments filed on 09/25/2024.
Claim Objections
Claim 1 is objected to because of the following informalities: “the image” in line 20 should read “the watermark image”. Appropriate correction is required.
Claim 5 is objected to because of the following informalities: “the image” in line 8 should read “the target image”. Appropriate correction is required.
Claim 6 is objected to because of the following informalities: “the image” in lines 3-4 should read “the target image”. Appropriate correction is required.
Claim 7 is objected to because of the following informalities: “removing an edge part of the target image first” in line 2 should read “first removing an edge part of the target image”. Appropriate correction is required.
Claim 11 is objected to because of the following informalities: “the image” in line 22 should read “the watermark image”. Appropriate correction is required.
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.
Claims 5, 16 and 22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by NPL1 (Watermark Image Restoration Method Based on Block Hopfield Network, Xiaohong Ma et al., Springer, 2009, Pages 365-370) hereafter NPL1.
1. Regarding claim 5, NPL1 discloses a watermark restoration method (page 366, section 2 and fig 1 shows a watermark restoration method), comprising:
acquiring a target image, and cropping the target image to obtain a plurality of target image blocks with position rankings (page 366, fig 1 and sections 2.1-2.2 shows and discloses “each watermark image (i.e acquiring a target image) is divided into MxM size of adjacent and non-overlapped (i.e with position rankings) sub-blocks (i.e target image blocks) meeting the above claim limitations);
respectively processing the plurality of target image blocks by calling a pre-trained watermark restoration model to obtain restored image blocks corresponding to the target image blocks (pages 366-367, fig 1, section 2.5 equation 2 Bpk(t+1)=sgn(Wk.Bpk(t)), t=0,1,2----shows and discloses all restored sub-block image vectors are combined together to generate the restored watermark image Bp using pretrained watermark restoration model as in fig 1 meeting the limitations of respectively processing the plurality of target image blocks by calling a pre-trained watermark restoration model to obtain restored image blocks corresponding to the target image blocks);
wherein, the watermark restoration model is trained based on a watermark image set synthesized by predefined watermark style information and background style information, and the watermark restoration model is used for restoring visible-watermark characters in the image (fig 2 shows the three original watermark images a, b, and c with the watermark style information and the corresponding background style information used in the restoration model of fig 1 and fig 3 shows the corresponding restored watermark images meeting the above claim limitations, examiner notes that the specifics of watermark style and background style are not required by the current claim); and
according to the position rankings of the plurality of target image blocks, performing position stitching on the restored image blocks corresponding to the target image blocks to obtain a target image restoration result (pages 366-367, fig 1, section 2.5 equation 2 Bpk(t+1)=sgn(Wk.Bpk(t)), t=0,1,2----shows and discloses the image A’p is divided into MxM size of adjacent and non-overlapped sub-block images A’pk all restored sub-block image vectors are combined (position stitched) together to generate the restored watermark image Bp (target image restoration result) meeting the above claim limitations).
2. Claim 16 is a corresponding non-transitory computer-readable storage claim of claim 5. See the explanation of claim 5. Examiner notes that a non-transitory computer readable storage medium is implied in view of the system in fig 1.
3. Claim 22 is a corresponding electronic device claim of claim 5. See the explanation of claim 5. Examiner notes that an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, the processor, when executing the program, implements the method according to claim 5 is implied in view of the system in fig 1.
Allowable Subject Matter
Claim 1 is allowed after correcting the minor informalities pointed out above.
Regarding independent claim 1, NPL1 discloses in pages 366-368, figs 1-2, A training method for a watermark restoration model, comprising: acquiring watermark style information and background style information, the watermark style information being used for indicating a visible-watermark character content style and the background style information being used for indicating a background image content style; generating a watermark image set according to a combination of the watermark style information and the background style information, the watermark image set comprising a plurality of images with visible watermarks;”.
Regarding claim 1, CN11346029A in paras 0012-0018, 0040-0043 (attached English translation) also discloses A training method for a watermark restoration model, comprising: acquiring watermark style information and background style information, the watermark style information being used for indicating a visible-watermark character content style and the background style information being used for indicating a background image content style; generating a watermark image set according to a combination of the watermark style information and the background style information, the watermark image set comprising a plurality of images with visible watermarks;”.
Regarding independent claim 1, NPL1 and CN11346029A alone or in combination however fail to disclose “compressing a watermark image in the watermark image set to obtain a corresponding watermark compressed image, and respectively cropping the watermark image and the corresponding watermark compressed image to obtain a plurality of watermark image blocks corresponding to the watermark image and a plurality of watermark compressed image blocks in position correspondence with the watermark image blocks; by using the watermark compressed image blocks as training samples and using the watermark image blocks in position correspondence with the watermark compressed image blocks as sample labels, combining the training samples and the sample labels corresponding to the training samples to generate a training data set; and constructing a neural network model, and training the neural network model by means of a convergence acceleration algorithm by calling the training data set to obtain a neural network model meeting a training termination condition as a watermark restoration model, the watermark restoration model being used for restoring visible-watermark characters in the image.”, therefore claim 1 is allowed. Dependent claims 2-4, 10 and 19-21, depending from claim 1 are also allowed.
Claim 11 is allowed after correcting the minor informalities pointed out above.
Regarding independent claim 11, NPL1 discloses in pages 366-368, figs 1-2, A non-transitory computer-readable storage medium storing computer instructions, characterized in that, the computer instructions cause a computer to perform a training method for a watermark restoration model, comprising: acquiring watermark style information and background style information, the watermark style information being used for indicating a visible-watermark character content style and the background style information being used for indicating a background image content style; generating a watermark image set according to a combination of the watermark style information and the background style information, the watermark image set comprising a plurality of images with visible watermarks;”.
Regarding claim 11, CN11346029A in paras 0012-0018, 0040-0043 (attached English translation) also discloses A non-transitory computer-readable storage medium storing computer instructions, characterized in that, the computer instructions cause a computer to perform a training method for a watermark restoration model, comprising: acquiring watermark style information and background style information, the watermark style information being used for indicating a visible-watermark character content style and the background style information being used for indicating a background image content style; generating a watermark image set according to a combination of the watermark style information and the background style information, the watermark image set comprising a plurality of images with visible watermarks;”.
Regarding independent claim 11, NPL1 and CN11346029A alone or in combination however fail to disclose “compressing a watermark image in the watermark image set to obtain a corresponding watermark compressed image, and respectively cropping the watermark image and the corresponding watermark compressed image to obtain a plurality of watermark image blocks corresponding to the watermark image and a plurality of watermark compressed image blocks in position correspondence with the watermark image blocks; by using the watermark compressed image blocks as training samples and using the watermark image blocks in position correspondence with the watermark compressed image blocks as sample labels, combining the training samples and the sample labels corresponding to the training samples to generate a training data set; and constructing a neural network model, and training the neural network model by means of a convergence acceleration algorithm by calling the training data set to obtain a neural network model meeting a training termination condition as a watermark restoration model, the watermark restoration model being used for restoring visible-watermark characters in the image.”, therefore claim 11 is allowed. Dependent claims 13-15 depending from claim 11 are also allowed.
Claims 6-7, 17-18 and 23 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/JAYESH PATEL/
Primary Examiner
Art Unit 2677
/JAYESH A PATEL/Primary Examiner, Art Unit 2677
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