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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/12/2025 was filed and is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Objections
Claim 4 is objected to because of the following informalities: possible typo that states “the learner the machine learning” in line 2. In the interest of compact prosecution, “the learner” is being interpreted as being part of the machine learning. Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“a target image acquiring unit configured to” in claim 1, described in paragraph [0008, 0019] and implemented on hardware described in paragraphs [0013-0017, 0019-00020].
“an instruction object detecting unit configured to” in claim 1, described in paragraph [0021] and implemented on hardware described in paragraphs [0013-0017].
“an instruction determining unit configured to” in claim 1, described in paragraph [0028, 0029, 0061, 0062] and implemented on hardware described in paragraphs [0013-0017].
“a replacement processing unit configured to” in claim 1, described in paragraph [0008, 0031, 0038] and implemented on hardware described in paragraphs [0013-0017].
“a user edit processing unit configured to” in claim 7, described in paragraph [0008, 0019, 0039] and implemented on hardware described in paragraphs [0013-0017].
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claims 4 and 5 recites the limitation "the learner" in line 2 for both claims, there appears to be no mention of a “learner” in claim 1. There is insufficient antecedent basis for this limitation in the claim. In the interest of compact prosecution (in the event of amendments that fix this error), “the learner” will be interpreted as “a learner” that belongs to a machine learning algorithm.
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-3, 6, 8-12 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mendes (“Structure Editing of Handwritten Mathematics: Improving the Computer Support for the Calculational Method”, 2014).
Regarding claim 1, Mendes teaches An image processing system, comprising:
a target image acquiring unit configured to acquire as a target image a document image of a document (Mendes, pg 139, Figure 1, which shows a non-limiting example of “a target image a document image of a document”);
an instruction object detecting unit configured to detect a first instruction object (Mendes, see nearest image below, “semi-circle” handwritten gesture is being interpreted as a non-limiting example of a first instruction object that is detected) and a second instruction object (Mendes, pg 144, column 1, ¶1, reproduced below:
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. Figure 8 shows the second instruction object is involved, otherwise, there would be no change from (a) starting point to the result in Figure 8) in the target image among handwritten objects (Mendes, see nearest image above, which shows a non-limiting example of handwritten objects, such as in Figure 7 or 8) additionally written to the document (Mendes, see nearest image above, the semi-circle handwritten gesture is being interpreted as a non-limiting example involving “additionally written”), the first instruction object specifying a process target object (Mendes, see nearest image above, the end of the semi-circle specifies a process target object, as seen in the (b) drag-and-drop part of Figure 7), and the second instruction object specifying data used for a replacement process (Mendes, see nearest image above, which shows a non-limiting example of the “a” data being used to distribute itself to create Figure 8) of the process target object (Mendes, see nearest image above, the end of the semi-circle specifies a process target object, as seen in the (b) drag-and-drop part of Figure 7);
an instruction determining unit configured to determine the process target object (Mendes, see nearest image above, the end of the semi-circle specifies a process target object, as seen in the (b) drag-and-drop part of Figure 7, also a non-limiting example) specified by the detected first instruction object (Mendes, see nearest image above, “semi-circle” handwritten gesture is being interpreted as a non-limiting example of a first instruction object) and determine the data specified by the detected second instruction object (Mendes, see nearest image above, which shows a non-limiting example of the “a” data being used to distribute itself to create Figure 8); and
a replacement processing unit configured to perform a replacement process (Mendes, see nearest image above, Figure 7 (b) shows non-limiting example “b ^ c” being replaced, which results in Figure 8) of the determined process target object (Mendes, see nearest image above, Figure 7 (b) shows non-limiting example “b ^ c” as a determined process target) with the determined data in the target image (Mendes, see nearest image above, which shows a non-limiting example of the “a” data being used to distribute itself to create Figure 8).
Regarding claim 2, Mendes teaches The image processing system according to claim 1, wherein the first instruction object and the second instruction object have different shapes from each other (Mendes, see image in claim 1, the “semi-circle’, first instruction object, is different from “a”, which involves the second instruction object).
Regarding claim 3, Mendes teaches The image processing system according to claim 2, wherein the first instruction object is a strikethrough line (Mendes, pg 140, column 2, 2nd paragraph: “Some of the gestures available in the MST editor are similar to the gestures available in these tools (e.g. like in MathPad2, the scratch-out gesture is used to erase content)”. “Scratch-out” is being interpreted as involving “strikethrough line”); and the second instruction object is a surrounding line (Mendes, pg 143, column 2, last paragraph: “Examples of gestures that we have defined for editing tasks are the circle gesture, which is used to select the content inside the circle”. “Circle” is being interpreted as involving “surrounding line”).
Regarding claim 6, Mendes teaches The image processing system according to claim 1, wherein the instruction determining unit performs a character recognition process (Mendes, pg 142, column 1, ¶3: “handwriting recognition”) for an image area specified (Mendes, pg 144, Figure 7a, the “a” is a non-limiting example of the image area specified) by the second instruction object (Mendes, pg 144, Figure 7a, the “a” is a non-limiting example of the data specified by the second instruction object) and thereby determines text data (Mendes, pg 142, column 1, ¶3: “handwriting recognition”) described in the image area (Mendes, pg 144, Figure 7a, the “a” is a non-limiting example of the image area specified); and the replacement processing unit deletes (Mendes, pg 144, Figures 7 and 8, Figure 7b shows “b ^ c” being deleted when going from Figure 7 to Figure 8) the process target object (Mendes, pg 144, Figure 7b shows “b ^ c”, which is being interpreted as a non-limiting example of “the process target object”) and adds an object (Mendes, pg 144, going from Figure 7 to 8, the handwritten “a” is being interpreted as “an image object”) based on the determined text data at a position of the process target object in the target image (Mendes, pg 144, column 1, ¶1, reproduced below:
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. Figure 7 and 8 show a non-limiting example of “a” as the image based on text “a” that was added at the “b ^ c” position of the process target object).
Regarding claim 8, Mendes teaches The image processing system according to claim 1, wherein the instruction object detecting unit detects a first instruction object (Mendes, see nearest image below, “semi-circle” handwritten gesture is being interpreted as a non-limiting example of a first instruction object that is detected) and a second instruction object (Mendes, pg 144, column 1, ¶1, reproduced below:
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. Figure 8 shows the second instruction object is involved, otherwise, there would be no change from 7a starting point to the result in Figure 8) in the target image among handwritten objects (Mendes, see nearest image above, which shows a non-limiting example of handwritten objects, such as in Figure 7 or 8) additionally written to the document (Mendes, see nearest image above, the semi-circle handwritten gesture is being interpreted as a non-limiting example involving “additionally written”), the first instruction object specifying a process target object (Mendes, see nearest image above, the end of the semi-circle specifies a process target object, as seen in the (b) drag-and-drop part of Figure 7), and the second instruction object specifying a replacement object used for a replacement process (Mendes, see nearest image above, which shows a non-limiting example of the “a” replacement object being used to distribute itself to create Figure 8) of the process target object (Mendes, see nearest image above, the end of the semi-circle specifies a process target object, as seen in the (b) drag-and-drop part of Figure 7);
the instruction determining unit determines the process target object (Mendes, see nearest image above, the end of the semi-circle specifies a process target object, as seen in the (b) drag-and-drop part of Figure 7, also a non-limiting example) specified by the detected first instruction object (Mendes, see nearest image above, “semi-circle” handwritten gesture is being interpreted as a non-limiting example of a first instruction object) and determine the replacement object specified by the detected second instruction object (Mendes, see nearest image above, which shows a non-limiting example of the “a” replacement object being used to distribute itself to create Figure 8); and
the replacement processing unit performs a replacement process (Mendes, see nearest image above, Figure 7 (b) shows non-limiting example “b ^ c” being replaced, which results in Figure 8) of the determined process target object (Mendes, see nearest image above, Figure 7 (b) shows non-limiting example “b ^ c” as a determined process target) with the determined replacement object in the target image (Mendes, see nearest image above, which shows a non-limiting example of the “a” data being used to distribute itself to create Figure 8).
Regarding claim 9, Mendes teaches The image processing system according to claim 8, wherein the replacement processing unit (a) performs a character recognition process (Mendes, see nearest image below, “handwriting recognition” is being interpreted to involve “character recognition process”) for the replacement object (Mendes, pg 144, Figure 7, the “a” is being interpreted as a non-limiting example of “the replacement object”) specified by the second instruction object (Mendes, pg 144, Figure 7, the “a” is being interpreted as a non-limiting example that involves “the second instruction object”) and thereby converts the replacement object to text data (Mendes, pg 142, column 1, ¶3, reproduced below:
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. “handwriting recognition” is being interpreted to involve “character recognition process” that converts the handwritten “a” into “text data”), and (b) deletes (Mendes, see nearest image below, Figure 7b shows “b ^ c” being deleted when going from Figure 7 to Figure 8) the process target object (Mendes, see nearest image below, Figure 7b shows “b ^ c”, which is being interpreted as a non-limiting example of “the process target object”) and adds an image object (Mendes, see nearest image below, going from Figure 7 to 8, the handwritten “a” is being interpreted as “an image object”) based on the text data at a position of the process target object in the target image (Mendes, pg 144, column 1, ¶1, reproduced below:
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. Figure 7 and 8 show a non-limiting example of “a” as the image based on text “a” that was added at the “b ^ c” position of the process target object).
Regarding claim 10, Mendes teaches The image processing system according to claim 8, wherein the replacement processing unit deletes the process target object (Mendes, see nearest image below, “b ^ c” from Figure 7b is a non-limiting example of a process target object being deleted as it no longer appears in Figure 8) and adds as an image object the replacement object (Mendes, see nearest image below, “a” from Figure 7 is being interpreted as a non-limiting example of an image object that is used in the replacement to result in Figure 8) specified by the detected second instruction object (Mendes, see nearest image below, “a” from Figure 7 is being interpreted as involving “detected second instruction object”) at a position of the process target object in the target image (Mendes, pg 144, column 1, ¶1, reproduced below:
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. From Figure 7, the end of the semi-circle is a non-limiting example of the position of the process target object in the target image).
Regarding claim 11, Mendes teaches The image processing system according to claim 8, wherein the replacement processing unit determines an operation mode specified by a user (Mendes, pg 142, column 1, ¶3, reproduced below:
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. With or “without a recognizer” are being interpreted as two possible operation modes “specified by a user”);
if the operation mode is a first mode (Mendes, see pg 142 image above, “The library can be used even without a recognizer”, which is being interpreted as a first mode), the replacement processing unit deletes (Mendes, pg 144, going from Figure 7 to Figure 8, “b ^ c” is being interpreted as involving “deletes”) the process target object (Mendes, pg 144, going from Figure 7b, “b ^ c” is being interpreted as involving the process target object) and adds as an image object the replacement object (Mendes, pg 144, going from Figure 7 to Figure 8, “a” is be non-limiting example of the replacement image object) specified by the detected second instruction object (Mendes, pg 144, Figure 7, the image “a” is being interpreted as involving “second instruction object”) at a position of the process target object (Mendes, pg 144, Figure 7a, the end of the semi-circle is being interpreted as involving “position of the process target object”) in the target image (Mendes, pg 144, Figure 7a, is a non-limiting example that involves the target image); and
if the operation mode is a second mode (Mendes, see pg 142 image above, “handwriting recognition” and using the library with a recognizer, is being interpreted as a second mode), the replacement processing unit (a) performs a character recognition process (Mendes, see pg 142 image above, “handwriting recognition”) for the replacement object specified by the second instruction object (Mendes, pg 144, going from Figure 7 to Figure 8, “a” is be non-limiting example of the replacement image object specified by the second instruction object) and thereby converts the replacement object to text data (Mendes, see pg 142 image above, “handwriting recognition”) and (b) deletes the process target object (Mendes, pg 144, going from Figure 7 to Figure 8, “b ^ c” is being interpreted as involving “deletes the process target object”) and adds an image object based on the text data (Mendes, pg 144, going from Figure 7 to Figure 8, “a” is be non-limiting example of the replacement image object based on the text data) at a position of the process target object (Mendes, pg 144, Figure 7a, the end of the semi-circle is being interpreted as involving “position of the process target object”) in the target image (Mendes, pg 144, Figure 7a, is a non-limiting example that involves the target image).
Regarding claim 12, Mendes teaches The image processing system according to claim 9, wherein the replacement processing unit generates the image object so as to make a size of the image object agree with a size of the process target object (Mendes, pg 140, column 1, last paragraph: “This editor supports online recognition of handwritten mathematical expressions and as soon as a character is written, it is automatically rewritten as neat strokes in an appropriate position and size”. “Appropriate…size” is being interpreted as a non-limiting example of “make a size of the image object agree with a size of the process target object”).
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) 4 and 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mendes, in view of Kim (“Digital handwriting correction using deep learning”, 2023).
Regarding claim 4, Mendes teaches The image processing system according to claim 1,
that include the first and second instruction objects (Mendes, pg 144, Figure 6, shows non-limiting examples of first and second instruction objects)
However, Mendes does not appear to explicitly teach machine learning using training data for objects having a plural colors, plural line width, and plural shapes. Although, Mendes does teach handwriting recognition.
Pertaining to the same field of endeavor, Kim teaches
wherein for the learner the machine learning has been performed using as training data plural document images (Kim, pg 3, column 1, ¶2: “Using these data, we used printed word images to train CNN”. “CNN” is being interpreted as involving “machine learning”. “Word images” are being interpreted as involving plural document images)
having plural colors (Kim, see Figure 3 below, the shades of gray of the character examples shown are being interpreted as plural colors. Examiner recommends viewing the color figure, available at the following link: https://ieeexplore.ieee.org/abstract/document/10049853), plural line width (Kim, see Figure 3b below, which shows non-limiting examples of Korean characters with plural line widths. For example, the top characters are thicker than the thin characters on the bottom), and plural shapes (Kim, pg 3, Fig 3 and ¶1 of column 1, reproduced below:
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. The examples show the Korean characters that have a plural of shapes).
Mendes and Kim are considered to be analogous art because they are directed to handwriting and replacement of handwritten data. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for handwriting and replacement of handwritten data with segmentation of characters (as taught by Mendes) to include machine learning using training data for objects having a plural colors, plural line width, and plural shapes (as taught by Kim) because the combination provides an improvement to handwriting correction (Kim, Abstract). Further, it would be obvious to try as bounding boxes are common knowledge for object detection.
Regarding claim 5, Mendes teaches The image processing system according to claim 1, …
the instruction determining unit determines the process target object specified by the detected first instruction object (Mendes, pg 144, Figure 7a, which shows the end of the semi-circle points to the “process target object” that ), and determines the data specified by the detected second instruction object (Mendes, pg 144, Figure 7a, the “a” and “
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“ are being interpreted as non-limiting examples of the data specified by the detected second instruction object).
However, Mendes does not appear to explicitly teach bounding box of each of the detected objects.
Pertaining to the same field of endeavor, Kim teaches
… wherein for each of the detected objects (Kim, Figure 1, the bounding boxes are being interpreted as involving detected objects), the learner outputs at least classifications (Kim, pg 2, column 1, Section A: “We propose CNN font classification”. “CNN” shows “learner” is involved. “Font classification” is a non-limiting example of classifications) including the first and second instruction objects (Kim, Figure 1, the red bounding box is being interpreted as involving first instruction object as it points to what or where to replace. The corrected output shows the second instruction object is involved as the corrected replacement data), and a bounding box of each of the detected objects (Kim, Figure 1, middle, which shows bounding boxes on the detected objects, the handwritten objects);
on the basis of the bounding boxes (Kim, pg 1, column 1, Section 1, ¶3: “As shown in Fig. 1, our framework first takes a handwritten image and provides the recognized text and bounding box position through Optical Character Recognition (OCR). Then, the spelling check module corrects the wrong text in the sentence.”. Which shows on the basis of the bounding box, correction is accomplished)….
Mendes and Kim are considered to be analogous art because they are directed to handwriting and replacement of handwritten data. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for handwriting and replacement of handwritten data with segmentation of characters (as taught by Mendes) to include bounding box of each of the detected objects (as taught by Kim) because the combination provides an improvement to handwriting correction (Kim, Abstract). Further, it would be obvious to try as bounding boxes are common knowledge for object detection.
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mendes, in view of Shilman (“CueTIP: A Mixed-Initiative Interface for Correcting Handwriting Errors”, 2006).
Regarding claim 7, Mendes teaches The image processing system according to claim 1,
However, Mendes does not appear to explicitly teach “after the replacement process; wherein the user edit processing unit (a) performs changing the process target object or the data in accordance with the user operation, and (b) performs edit of the target image correspondingly to the changing”. Although, PHOSITA would know that a user may want to correct or change their mind about an operation. That’s why the “Undo” operation in most text-based software exists.
Pertaining to the same field of endeavor, Shilman teaches
further comprising a user edit processing unit configured to perform edit based on a user operation (Shilman, pg 326, first full paragraph: “When a user performs either of these operations”. Which is being interpreted as involving editing) for the target image (Shilman, pg 325, Figure 3, letters with the purple bar on top are the results, or a non-limiting example of the target image) after the replacement process (Shilman, pg 326, first full paragraph: ”When a user performs either of these operations, the recognizer is re-invoked with the original handwriting as well as any correction constraints that the user has specified (e.g. that a series of strokes were actually one word rather than two)”. After the user performs the editing, replacement happens. See Figure 3 for examples where a non-limiting example of “rewrite” as a replacement process);
wherein the user edit processing unit (a) performs changing the process target object (Shilman, pg 325, Figure 3, which shows the split row, the target “def” is changed to “d ef”, with a space in-between) or the data in accordance with the user operation (Shilman, pg 325, Figure 3, for the row with the rewrite operation, the “e” is being changed to “c”, the data is being changed.), and
(b) performs edit of the target image correspondingly to the changing (Shilman, pg 326, first full paragraph: ”When a user performs either of these operations, the recognizer is re-invoked with the original handwriting as well as any correction constraints that the user has specified (e.g. that a series of strokes were actually one word rather than two)”. Which shows the results can change again after another round of edits by the user.
Mendes and Kim are considered to be analogous art because they are directed to handwriting and handwriting correction. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for handwriting and replacement of handwritten data performed by a user (as taught by Mendes) to include after the replacement process; wherein the user edit processing unit (a) performs changing the process target object or the data in accordance with the user operation, and (b) performs edit of the target image correspondingly to the changing (as taught by Shilman) because the combination provides an improvement to handwriting error recovery (Shilman, Abstract). Further, Mendes already teaches user editing (scratching out as a form of deletion) and multiple user operations (see pg 145 where user selects and copies multiple times).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Bagley et al (US 5548700 A, 1993) discloses editing text in an image that includes handwriting.
Tamashima (US 8760680 B2, 2012) discloses instruction objects to add (stamp “confidential”) or replace (redact, or place a black bar over text) to printed documents with varying security levels.
Mendes Dissertation (“Structured Editing of Handwritten Mathematics”, 2012) discloses instruction objects for replacing text with user correction (interpreted from redo/undo).
Kiranagi et al (“Automation of Document Editing: A Vision Based Approach”, 2007) discloses recognition of instruction objects that then are used to edit text.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNY B DUONG whose telephone number is (571)272-1358. The examiner can normally be reached Monday - Thursday 10a-9p (ET).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached at (571)272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.B.D./Examiner, Art Unit 2667
/MICHAEL ROBERT CAMMARATA/Primary Examiner, Art Unit 2667
Prosecution Insights