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 .
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.
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention(s) is/are directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim recites “non-volatile computer-readable storage medium” and 1. the BRI of “computer-readable storage medium” encompasses transitory signals and waveforms and 2. the specification does not expressly exclude transitory signals and waveforms from the interpretation of “computer-readable storage medium.” Since transitory signals and waveforms do not fall within one of the four statutory categories of invention, the claim is non-statutory. A claim drawn to such a computer readable storage medium that covers both transitory and non-transitory embodiments may be amended to narrow the claim to cover only statutory embodiments to avoid a rejection under 35 U.S.C. § 101 by adding the limitation “non-transitory,” such as “non-transitory computer-readable storage medium,” to the claim.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 3-8,22-23 and 25 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 3 and 22 recite “short-circuiting”. It is not clear what Applicant means. Short-circuiting does not appear to be a term in the art of neural networks.
Claim 6 and 25 recites “a XXX direction perceptual map” followed by “the XXX directional perceptual map”, where XXX is first and second. These claim limitations lack antecedent basis.
Claims 4,7-8 and 23 are rejected as dependent upon a rejected claim.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2,19-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over “Real-time Scene Text Detection with Differentiable Binarization”, hereafter referred to as Liao, in view of “Image compression based on octave convolution and semantic segmentation” hereafter referred to as Liu.
Liao discloses 1.A text recognition method, comprising:
acquiring
performing an M-level convolution process on the
merging the M pairs of target (Liao, Fig. 3 ,
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Concat reads on merging; pairs of data; Liao takes an image and perform)
determining a probability map and a threshold map of the target image based on the target feature map, and calculating a binarization map of the target image based on the probability map and the threshold map; and determining a text area in the target image based on the binarization map, and recognizing text information in the text area. (Liao, Fig. 3,
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; see probablity map, threshold map, binary map and the determined text)
Liao discloses normal convolution, but does not expressly disclose octave convolution, in particular
“acquiring a first high-frequency feature map and a first low-frequency feature map of a target image;
performing an M-level convolution process on the first high-frequency feature map and the first low-frequency feature map by M cascaded convolution modules to obtain M pairs of target high-frequency feature map and target low-frequency feature map of the target image, where M is a positive integer;
merging the M pairs of target high-frequency feature map and target low-frequency feature map to obtain a target feature map of the target image;”
Liu discloses “acquiring a first high-frequency feature map and a first low-frequency feature map of a target image;
performing an M-level convolution process on the first high-frequency feature map and the first low-frequency feature map by M cascaded convolution modules to obtain M pairs of target high-frequency feature map and target low-frequency feature map of the target image, where M is a positive integer;
merging the M pairs of target high-frequency feature map and target low-frequency feature map to obtain a target feature map of the target image;”(Liu, pg. 1-2,
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Fig. 1. On the left is octave convolution, where f(·) is vanilla convolution, W is convolution kernel, pool(·) is average pooling, and upsample(·) is an up-sampling using nearest neighbor interpolation.)
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to replace the standard convolution of Liao with the octave convolution of Liu.
The suggestion/motivation for doing so would have been to decrease the number of calculations and storage space.
Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liao with Liu to obtain the invention as specified in claim 1.
Liao in view of Liu discloses 2. The text recognition method according to claim 1, wherein the convolution module performs a convolution process on the first high-frequency feature map and the first low-frequency feature map, and the convolution process comprises: performing a first convolution process on the input first high-frequency feature map to obtain a second high-frequency feature map, and performing an up-sampling convolution process on the input first low-frequency feature map to obtain a second low-frequency feature map; acquiring the target high-frequency feature map based on the second high-frequency feature map and the second low-frequency feature map; performing a second convolution process on the input first low-frequency feature map to obtain a third low-frequency feature map, and performing a down-sampling convolution process on the input first high-frequency feature map to obtain a third high-frequency feature map; and acquiring the target low-frequency feature map based on the third low-frequency feature map and the third high-frequency feature map. (Liu, Fig. 1
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Fig. 1. On the left is octave convolution, where f(·) is vanilla convolution, W is convolution kernel, pool(·) is average pooling, and upsample(·) is an up-sampling using nearest neighbor interpolation )
Claim 19 is rejected under similar grounds as claim 1.
Claim 20 is rejected under similar grounds as claim 1.
Claim 21 is rejected under similar grounds as claim 2.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Liao in view of Lui in further view of “AMultiplexed Network for End-to-End, Multilingual OCR”, hereafter referred to as Huang.
Liao in view of Liu discloses 11. The text recognition method according to claim 1,
But doesn’t expressly disclose “wherein the method further comprises: predicting a language in which the target image contains text based on the target feature map; and the recognizing of the text information in the text area comprises: determining a corresponding text recognition model according to the language in which the target image contains the text to recognize the text information in the text area.”
Huang discloses “wherein the method further comprises: predicting a language in which the target image contains text based on the target feature map; and the recognizing of the text information in the text area comprises: determining a corresponding text recognition model according to the language in which the target image contains the text to recognize the text information in the text area.” (Huang, Fig. 1,
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It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to add the language detection and selection of language model of Huang to the system of Liao in view of Liu.
The suggestion/motivation for doing so would have been to provide translations for the users.
Further, one skilled in the art could have combined the elements as described above by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liao in view of Lui and Huang to obtain the invention as specified in claim 11.
Allowable Subject Matter
Claims 3-10, 12-18, 22-27 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, if asserted, as set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GANDHI THIRUGNANAM whose telephone number is (571)270-3261. The examiner can normally be reached M-F 8:30-5PM.
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/GANDHI THIRUGNANAM/Primary Examiner, Art Unit 2672