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 .
The following action is in response to the amendment and remarks of 06/30/2026.
By the amendment, claims 1, 9, 10 and 15 have been amended. Claims 19-20 have been canceled.
Claims 1-18 are pending and have been considered below.
Response to Arguments
The 35 USC 112(a) rejection of claims 1-20 (Non-Final Rejection 04/01/2026) has been withdrawn in light of the amendment and corresponding remarks.
Applicant argues, with respect to amended claim 1, that the features of claim 9 which were added to the independent claim are not taught by Wimmer; particularly that Wimmer is silent regarding any extraction of numerical value indicating merging and/or separating. The Examiner respectfully disagrees. Wimmer discloses (col 9 lines 19-30) at least a trained neural network SVM having an extra class (2-class supervised learning model). Wimmer discloses that the neural network is used to rejection nodes considered bad segmentation (col 9 lines 19-21). Using probability and recognition scores for he nodes which have numerical values (col 9 lines 64-67, Fig. 6), Wimmer determines whether to group or separate (col 7 lines 54-64, col 8 lines 15-25). This anticipates the claim as amended. The argument is not persuasive.
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 1-6, 8, and 10-18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wimmer et al., US 9,911,052 B2 published 03/06/2018 [“WIMMER”].
Regarding claim 1, WIMMER discloses a electronic device, comprising:
a display;
at least one processor; and
memory storing instructions that, when executed by the at least one processor individually or collectively (Fig. 1, col 5 line 40 – col 7 line 41), cause the electronic device to:
receive a handwriting input including overwritten characters through the display (col 7 lines 32-41: receive superimposed characters through handwriting input, Fig. 3A, col 2 lines 46-47);
extract feature information from the handwriting input (col 7 lines 42-51, col 9 lines 53-56: segmentation expert, language expert and recognition expert work in collaboration, Fig. 2, col 9 lines 4-14: recognition expert performs feature extraction);
cause a machine learning algorithm related to character separation to merge or separate a series of consecutive strokes of the handwriting input including the overwritten characters based on the feature information (col 7 lines 54-61: segmentation expert groups consecutive strokes, Fig. 3B, col 10 lines 9-19: machine learning algorithm, col 10 lines 14-19: segmentation, recognition and interpretation performed concurrently), wherein the overwritten characters comprise a subsequently written character on top of a prior written character, wherein, during an overwrite mode, the machine learning algorithm supports recognition of the overwritten characters stacked on top of one another within a same writing area (col 8 lines 26-35: character sequence performed in superimposed area, Fig. 3A, Fig. 4), wherein the machine learning algorithm is trained based on a 2-class supervised learning method (col 9 lines 19-23: neural network comprising an extra class) that extracts a first numerical value indicating merging and extracts a second numerical value indicating the separating (col 9 lines 15-30: SVM algorithm used to rejection node hypothesis using probabilities and recognitions scores for each node, col 9 lines 64-67: node have values used in cost analysis for determining action, Fig. 6: numerical values associated with nodes, col 7 lines 54-64, col 8 lines 15-25: grouping/merging or separating actions for nodes based on n-gram costs); and
perform handwriting recognition based on a result of performing the merging or the separating (col 9 lines 53-56: output recognition candidates).
Regarding claim 2, WIMMER discloses electronic device of claim 1, wherein the instructions are configured to enable the electronic device to extract the feature information between a predesignated number of strokes among the series of consecutive strokes (col 9 lines 6-14).
Regarding claim 3, WIMMER discloses the electronic device of claim 1, wherein the feature information between the series of consecutive strokes includes at least one of a straightness of a stroke, a slope angle of the stroke, position information about a start point of the stroke, a slope angle of a virtual ligature, or a length ratio of the virtual ligature (col 9 lines 6-14).
Regarding claim 4, WIMMER discloses the electronic device of claim 1, wherein the machine learning algorithm is trained (col 10 lines 9-14) using overwritten character samples and normal sentence samples to perform the character separation on overwritten characters or characters of a normal sentence (col 8 lines 15-25), the overwritten character samples comprising first characters written on top of second characters such that the first characters and the second characters are cover a portion of a same space (col 8 lines 26-35).
Regarding claim 5, WIMMER discloses the electronic device of claim 4, wherein the instructions are configured to enable the electronic device to use at least one of a multi-layer-perceptron (MLP), a support vector machine (SVM), or deep learning for training the machine learning algorithm (col 9 lines 15-30).
Regarding claim 6, WIMMER discloses the electronic device of claim 1, wherein the instructions are configured to enable the electronic device to display a handwriting recognition result corresponding to the handwriting input on the display based on the result of performing the merging or the separating through a handwriting recognition engine (col 9 lines 55-56).
Regarding claim 8, WIMMER discloses the electronic device of claim 1, wherein the instructions are configured to enable the electronic device to:
perform pre-processing on the handwriting input received (col 7 lines 43-48); and
extract the feature information between the series of consecutive strokes corresponding to the handwriting input that is pre-processed (col 7 lines 48-51, col 9 lines 4-14).
Regarding claims 10-14, claims 10-14 recite limitations similar to claims 1-5, respectively, and are similarly rejected.
Regarding claim 15, claim 15 recites limitations similar to claim 1 and is similarly rejected.
Regarding claim 16, WIMMER discloses the electronic device of claim 1, wherein the instructions are configured to enable the electronic device to identify straightness and slope angle using a first point and a last point of each of the strokes constituting the handwriting input and extract the feature information including the straightness and the slope angle (col 9 lines 8-11).
Regarding claim 17, WIMMER discloses the electronic device of claim 1, wherein the instructions are configured to enable the electronic device to identify position information about a start point of each stroke based on a first point and a last points of each stroke and extract the feature information including the position information (col 9 lines 8-11).
Regarding claim 18, WIMMER discloses the electronic device of claim 1, wherein the instructions are configured to enable the electronic device to identify a feature of a virtual ligature between last points of strokes, and extract the feature information including position information about each stroke based on a first point and last point of each stroke, and extract the feature information including a slope angle of the virtual ligature and a length ratio of the virtual ligature (col 9 lines 8-11).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over WIMMER in view of Kienzle et al., US 9,881,224 B2 published 01/30/2018 [“KIENZLE”].
Regarding claim 7, WIMMER discloses the electronic device of claim 1, wherein the instructions are configured to enable the electronic device to:
display the handwriting input on a first portion of the display (col 1 lines 30-51, Fig. 3A, col 3 lines 4-6);
convert a handwriting recognition result corresponding to the handwriting input into text (col 3 lines 19-30); and
display the text on the display (col 3 lines 32-33: output).
WIMMER fails to explicitly disclose wherein the displayed text is displayed on a second portion of the display.
KIENZLE discloses methods for recognizing and displaying output for overlapping handwriting inputs (col 2 lines 32-51). In particular, KIENZLE discloses the overlapping handwriting being displayed on a first portion of the display and the recognized output being displayed on a second portion of the display (col 5 lines 16-27, lines 45-54, Fig. 1). Therefore it would have been obvious to one having ordinary skill in the art and the teachings of WIMMER and KIENZLE before them before the effective filing of the claimed invention to combine the outputting of recognized overlapping handwriting in a second portion of the display, as suggested by KIENZLE, with the output of the recognized overlapping handwriting of WIMMER. One would have been motivated to make this combination in order to automatically populate form fields of the UI based on the user handwriting inputs to provide real-time visual feedback without the need or use of a virtual keyboard, as suggested by KIENZLE (col 14 lines 25-51).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Wimmer in view of Kang et al., US 2014/0300609 A1 [“KANG”].
Regarding claim 9, WIMMER discloses the electronic device of claim 1, and further discloses wherein the instructions are configured to enable the electronic device to extract two consecutive strokes from a series of consecutive strokes in order to extract feature information between the two consecutive strokes, such that if the two consecutive strokes are extracted from the same character the two consecutive strokes are processed as merged and if the two consecutive strokes are extracted from different characters the two consecutive strokes are processed as separated (col 7 lines 54-67).
While WIMMER discloses extracting numerical values indicating merging and separating, WIMMER fails to disclose wherein the two consecutive strokes are extracted from the same character when the two consecutive strokes have a same index value and the two consecutive strokes are extracted from the different characters when the two consecutive strokes have different index values.
KANG discloses methods for determining handwriting from stroke information (pp. 12). In particular, KANG discloses determining consecutive strokes are from the same character when they have a same index value and from different characters if they have different index values (pp. 134: if overlapped length between two strokes are greater than or equal to a reference/index value, the strokes are considered one stroke block, otherwise they are not). Therefore it would have been obvious to one having ordinary skill in the art and the teachings of WIMMER and KANG before them before the effective filing of the claimed invention to combine the index value comparison for determining consecutive strokes as the same character, as taught by KANG, with the values for determining consecutive stroke characters of WIMMER. One would have been motivated to make this combination in order to provide alternate methods of disambiguating stroke segments (pp. 15) when editing digital documents, providing additional functionality to a user, as suggested by KANG (pp. 8-9).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mowen, Jonas et al.
CN 102243570 A
METHOD AND APPARATUS FOR ON-TOP WRITING
Loudon, Gareth H. et al.
US 20030190074 A1
METHODS AND APPARATUSES FOR HANDWRITING RECOGNITION
Maruyama; Kosuke et al.
US 20130136360 A1
IMAGE PROCESSING APPARATUS, IMAGE PROCESSING METHOD, AND COMPUTER READABLE MEDIUM
Hébert; David
US 20210034848 A1
SYSTEM AND METHOD FOR TEXT LINE EXTRACTION
Hébert; David
US 20230096728 A1
SYSTEM AND METHOD FOR TEXT LINE AND TEXT BLOCK EXTRACTION
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW L TANK whose telephone number is (571)270-1692. The examiner can normally be reached Monday-Thursday 9a-6p.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Ell can be reached at 571-270-3264. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW L TANK/Primary Examiner, Art Unit 2141
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