DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Applicant’s election of Group I in the reply filed on 6/10/2026 is acknowledged. Because applicant did not distinctly and specifically point out the supposed errors in the restriction requirement, the election has been treated as an election without traverse (MPEP § 818.01(a)). The application has pending claim(s) 1-17 (non-elected claims 5-14 and 17 are withdrawn from further consideration).
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claims 1 and 15-16 are objected to because of the following informalities:
Claim 1 at line 6; and claim 15 at line 4; and claim 16 at line 3 respectively: “table;” should be -- table image; --.
Appropriate correction is required.
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.
Claims 1-3 and 15-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without integration into a practical application or recitation of significantly more.
In the analysis below, the device of independent claim 1 and similarly the non-transitory computer-readable storage medium of independent claim 15 and the method of claim 16 are directed to one of the four statutory categories of eligible subject matter; thus, the claims pass Step 1 of the Subject Matter Eligibility Test (See flowchart in MPEP 2106).
Step 2A, prong 1 analysis
The independent claims are directed to “specifying a plurality of pairs each consisting of two objects selected from the extracted objects; performing set determination to determine whether or not the pairs are each a set constituting a component of the table; performing same-row determination to determine whether or not the objects of each of the pairs shares a same row; performing same-column determination to determine whether or not the objects of each of the pairs shares a same column; and determining a structure of the table by specifying a row and a column to which each of the objects belongs from a result of the set determination, a result of the same-row determination, and a result of the same-column determination”.
Each of the above limitations of “specifying a plurality of pairs each consisting of two objects selected from the extracted objects”, “performing set determination to determine whether or not the pairs are each a set constituting a component of the table”, “performing same-row determination to determine whether or not the objects of each of the pairs shares a same row”, “performing same-column determination to determine whether or not the objects of each of the pairs shares a same column”, and “determining a structure of the table by specifying a row and a column to which each of the objects belongs from a result of the set determination, a result of the same-row determination, and a result of the same-column determination” as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the human mind which falls within the “Mental Processes” grouping of abstract ideas.
Additional elements
The additional elements recited in independent claim 1 are the elements of “a processor to execute a program” and “a memory to store the program which, when executed by the processor, performs processes” and the additional elements recited in independent claim 15 are the elements of a “non-transitory computer-readable storage medium storing a program that causes a computer to execute processing”. The independent claims also include the additional element of “analyzing a table image representing a table to extract a plurality of objects included in the table”.
Step 2A, prong 2 analysis
The above-identified additional elements do not integrate the judicial exception into a practical application.
The step “analyzing a table image representing a table to extract a plurality of objects included in the table” merely constitutes activity involving data gathering. Such extra-solution activity does not integrate the abstract idea into a practical application. Please see MPEP §2106.05(g).
The other additional elements “a processor to execute a program”, “a memory to store the program which, when executed by the processor, performs processes”, and a “non-transitory computer-readable storage medium storing a program that causes a computer to execute processing” amounts to merely using a computer as a tool to perform the claimed mental process. Implementing an abstract idea on a computer does not integrate a judicial exception into a practical application (See MPEP 2106.05(f)).
Moreover, the additional elements of the claims do not recite an improvement in the functioning of a computer or other technology or technical field, the claimed steps are not performed using a particular machine, the claimed steps do not effect a transformation, and the claims do not apply the judicial exception in any meaningful way beyond generically linking the use of the judicial exception to a particular technological environment (See MPEP 2106.04(d)). Therefore, the analysis under prong two of step 2A of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
Step 2B
Finally, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As noted above, the step of “analyzing a table image representing a table to extract a plurality of objects included in the table” amounts to insignificant extra-solution activity. Such insignificant extra-solution activity does not constitute significantly more than the claimed data gathering (See MPEP 2106.05(g)).
The other additional elements “a processor to execute a program”, “a memory to store the program which, when executed by the processor, performs processes”, and a “non-transitory computer-readable storage medium storing a program that causes a computer to execute processing” are generic computer features which perform generic computer functions that are well-understood, routine, and conventional and do not amount to more than implementing the abstract idea with a computerized system. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea).
Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation, and mere implementation on a generic computer does not add significantly more to the claims. Accordingly, the analysis under step 2B of the Subject Matter Eligibility Test does not result in a conclusion of eligibility (See flowchart in MPEP 2106).
For all of the foregoing reasons, independent claims 1, 15, and 16 do not recite eligible subject matter under 35 USC 101.
Regarding Dependent Claims 2-3:
Claims 2-3 are dependent on corresponding independent claim 1 respectively and therefore include all the limitations of corresponding independent claim 1. Thus claims 2-3 recites “Mental Processes”. Further, claims 2-3 further describes:
Dependent claim 2 merely describes “determines that objects of a set pair share a same row, the set pair being a pair determined to be a set through the set determination” and “determines that the objects of the set pair share a same column” which are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the human mind which falls within the same “Mental Processes” grouping of abstract ideas and it does not integrate the abstract idea into a practical application or add significantly more.
Dependent claim 3 merely describes “learns a set determination model by using training data including input data and truth data, the set determination model being a learning model that performs the set determination, the input data indicating a learning pair consisting of two objects, the truth data indicating whether or not the learning pair is a set” and “… uses the set determination model to perform the set determination” which are processes that due to their broad generality amount to merely using a generic computer as a tool to implement generic computer functions [e.g. learning a model using training data including ground truth data of the particular in use data respectively] that are well-understood, routine, and conventional and do not amount to more than implementing the abstract idea with a computerized system which neither integrates the abstract idea into a practical application nor adds significantly more.
Thus, claims 2-3 do not recite eligible subject matter under 35 USC 101.
Regarding Claim 4:
Claim 4 is dependent on claim 3 respectively and therefore includes all the limitations of claims 1 and 3. Thus claim 4 recites “Mental Processes”. Claim 4 further recites additional elements:
“specifies a position and a type of each of the objects, and the set determination model is a model that performs binary classification to classify whether two determination target objects subjected to the set determination are a set through a neural network receiving a tensor as input, the tensor being obtained by superposing two mask images and the table image, the two mask images having pixel values for areas corresponding to the positions of the two determination target objects, the pixel values indicating the types of the two determination target objects”.
The combination of the additional elements integrates the “Mental Processes” abstract idea into a practical application. Specifically, as discussed in paragraph “Examples that can be applied …” in page 14 through paragraph “By inputting not only …” in page 15 of the originally filed specification of the subject application, such processes provide higher accuracies in the determination and thereby constitutes an improvement to the technical field of the table-image recognition. As such, the additional elements of claim 4 integrate the “Mental Processes” into a practical application. Therefore, claim 4 recites eligible subject matter.
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 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Baek et al (WO 2022182111 A1, the attached English language translation is used hereinafter as the Official English language translation of this WO document).
Re Claim 1: Baek discloses a table-image recognition device (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last three paragraphs of Page 25/93, first paragraph of Page 26/93) comprising: a processor to execute a program (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last three paragraphs of Page 25/93, first paragraph of Page 26/93); and a memory to store the program which, when executed by the processor, performs processes of (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last three paragraphs of Page 25/93, first paragraph of Page 26/93), analyzing a table image representing a table to extract a plurality of objects included in the table (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, receiving an image including a table and recognizing a plurality of cells constituting the table); specifying a plurality of pairs each consisting of two objects selected from the extracted objects (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, specifying and performing pairing); performing set determination to determine whether or not the pairs are each a set constituting a component of the table (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, determining relationship); performing same-row determination to determine whether or not the objects of each of the pairs shares a same row (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, lines 28-29 of Page 27/93, paragraphs 3-8 of Page 21/93, same row determination); performing same-column determination to determine whether or not the objects of each of the pairs shares a same column (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, lines 28-29 of Page 27/93, paragraphs 3-8 of Page 21/93, same column determination); and determining a structure of the table by specifying a row and a column to which each of the objects belongs from a result of the set determination, a result of the same-row determination, and a result of the same-column determination (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, lines 28-29 of Page 27/93, paragraphs 3-8 of Page 21/93, structure of the table determination).
Although different embodiments of Baek have been referred to, it would have been exceedingly obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Baek by combining Baek’s similar embodiments in order to not limit the embodiments to themselves but include other evident combinations and extensions thereof (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last three paragraphs of Page 25/93, first two paragraphs of Page 26/93).
Re Claim 2: Baek further discloses wherein, the processor determines that objects of a set pair share a same row, the set pair being a pair determined to be a set through the set determination (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, lines 28-29 of Page 27/93, paragraphs 3-8 of Page 21/93, specifying the relationship, determining same row), and the processor determines that the objects of the set pair share a same column (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, lines 28-29 of Page 27/93, paragraphs 3-8 of Page 21/93, specifying the relationship, determining same column).
As to claim 15, the claim is the corresponding non-transitory computer-readable storage medium claim to claim 1 respectively. The discussions are addressed with regard to claim 1. Further, Baek further discloses a non-transitory computer-readable storage medium storing a program that causes a computer to execute processing of the processes (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last three paragraphs of Page 25/93, first paragraph of Page 26/93).
As to claim 16, the claim is the corresponding method claim to claim 1 respectively. The discussions are addressed with regard to claim 1. Further, Baek further discloses a table-image recognition method comprising the processes (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last three paragraphs of Page 25/93, first paragraph of Page 26/93).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Baek in view of Price et al (US 2020/0151444 A1). The teachings of Baek have been discussed above.
Re Claim 3: Baek further discloses wherein, the processor learns a set determination model by using training data including input data, the set determination model being a learning model that performs the set determination, the input data indicating a learning pair consisting of two objects (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, lines 7-8 of Page 20/93, determining relationship based on the deep learning algorithm learnt / trained using relationship data); and the processor uses the set determination model to perform the set determination (see Baek, last paragraph of Page 3/93, first two paragraphs of Page 4/93, last paragraph of Page 4/93, lines 7-8 of Page 20/93, determining relationship based on the deep learning algorithm).
However Baek fails to explicitly disclose wherein Price discloses learns a model by using training data that also includes truth data wherein the truth data indicating whether or not the learning pair is a set (see Price, [0072], [0079], [0088], [0107], the input structure is based on the ground truth structure for the training tables, the ground truth structure being known as part of the set of training tables).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Baek’s device using Price’s teachings by including the ground truth training process to Baek’s learning / training process in order to improve the accuracy of identifying the table (see Price, [0072], [0079], [0088], [0107]).
Allowable Subject Matter
Claim 4 is 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Jain et al ‘391 discloses table structure recognition via deep spatial association of words using an optimal number of word pairs and ground truth; Yu et al ‘014 discloses text-based machine learning extraction of table data from a document; Zhang ‘975 discloses a table structure recognition; Yang et al ‘300 discloses a table structure recognition method based on image recognition.
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/Bernard Krasnic/Primary Examiner, Art Unit 2671 July 14, 2026
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