# US 10,482,174 B1 · Systems and methods for identifying form fields > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,482,174 B1 - Document ID: US10482174B1 - Status: Granted - Kind: B1 - Application number: 16/163,537 - Filed: 2018-10-17 - Granted: 2019-11-19 - Earliest claimed: 2018-10-17 - Assignees: Capital One Services, LLC - Applicants: Capital One Services, LLC - Inventors: Jeremy Goodsitt; Austin Walters; Vincent Pham; Mark Watson; Anh Truong; Fardin Abdi Taghi Abad; Reza Farivar; Kate Key - Web page: https://patentgrep.com/patent/US10482174B1 ## CPC - G06V 10/82: using neural networks - G06F 16/313: {Selection or weighting of terms for indexing} - G06F 16/35: Clustering; Classification - G06F 40/174: Form filling; Merging - G06F 40/186: Templates - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/0475: Generative networks - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - G06N 3/094: Adversarial learning - G06N 3/096: Transfer learning - G06N 3/0985: Hyperparameter optimisation; Meta-learning; Learning-to-learn - G06V 30/19173: {Classification techniques} - G06V 30/412: Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables - G06V 30/416: Extracting the logical structure, e.g. chapters, sections or page numbers; Identifying elements of the document, e.g. authors - G06N 3/044: Recurrent networks, e.g. Hopfield networks - G06N 3/045: Combinations of networks - G06N 3/048: Activation functions - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract The present disclosure relates to systems and methods for generating synthetic documents. In one implementation, a system for generating synthetic data from a plurality of documents may include at least one processor and at least one non-transitory memory storing instructions that, when executed by the at least one processor cause the system to: receive a plurality of documents, individual documents of the plurality of documents having a same document type; generate a distribution of values for a corresponding pixel in the individual documents of plurality of documents; determine, based on the distributions, one or more common features of the plurality of documents; determine, based on the comparison, one or more input fields; generate a template including the one or more common features and the one or more input fields; and input synthetic data into the one or more input fields of the template thereby generating a plurality of synthetic documents. ## Claims ### Claim 1 A system for generating a synthetic document from a plurality of documents comprising: at least one processor; and at least one non-transitory memory storing instructions that, when executed by the at least one processor cause the system to perform operations comprising: receiving a plurality of documents, individual documents of the plurality of documents having a same document type; generating a distribution of values for a pixel at a corresponding location in the individual documents of plurality of documents; determining, based on the distribution, one or more common features of the plurality of documents; determining, based on a comparison of a pixel at the corresponding location in an individual document to the distribution, one or more input fields; generating a template including the one or more common features and the one or more input fields; and inputting synthetic data into the one or more input fields of the template thereby generating at least one of a plurality of synthetic documents. ### Claim 2 (depends on 1) The system of claim 1, wherein the operations further comprise at least one of aligning or rotating one or more of the plurality of documents. ### Claim 3 (depends on 1) The system of claim 1, wherein the operations further comprise generating an expected background based on the one or more common features. ### Claim 4 (depends on 1) The system of claim 1, wherein the document type comprises at least one of a loan application, an account application, a public document, an identification card, or a passport. ### Claim 5 (depends on 1) The system of claim 1, wherein the operations further comprise performing a background subtraction operation on one or more documents of the plurality of documents. ### Claim 6 (depends on 1) The system of claim 1, wherein a corresponding pixel comprises a pixel having the same location in the plurality of documents. ### Claim 7 (depends on 1) The system of claim 1, wherein determining one or more common features comprises identifying a set of pixels, the pixels being associated with a distribution having less than a threshold standard deviation. ### Claim 8 (depends on 1) The system of claim 1, wherein determining one or more input fields comprises identifying a set of pixels, the pixels being associated with a distribution having greater than a threshold standard deviation. ### Claim 9 (depends on 8) The system of claim 8, wherein an input field comprises an outer boundary of a set of adjacent pixels. ### Claim 10 (depends on 1) The system of claim 1, wherein determining one or more input fields comprises performing pattern recognition. ### Claim 11 (depends on 10) The system of claim 10, wherein pattern recognition comprises identifying at least one of a check box, a line, a box, or a prompt. ### Claim 12 A computer-implemented method for generating synthetic documents, comprising: receiving, by a processor, a plurality of documents, individual documents of the plurality of documents having a same document type; generating a distribution of values for a pixel at a corresponding location in individual documents of the plurality of documents; determining, based on the distribution, one or more common features of the plurality of documents; determining, based on a comparison of a pixel at the corresponding location in an individual document to the distribution, one or more input fields; generating a template including the one or more common features and the one or more input fields; and inputting synthetic data into the one or more input fields of the template thereby generating at least one of a plurality of synthetic documents. ### Claim 13 (depends on 12) The method of claim 12, further comprising generating an expected background based on the one or more common features. ### Claim 14 (depends on 13) The method of claim 13, wherein the expected background comprises a plurality of pixels, a pixel corresponding to a pixel position in the plurality of documents. ### Claim 15 (depends on 14) The method of claim 14, wherein each of the plurality of pixels comprises a mean of the distribution associated with the corresponding pixel. ### Claim 16 (depends on 12) The method of claim 12, further comprising determining metadata associated with one or more documents of the plurality of documents. ### Claim 17 (depends on 16) The method of claim 16, wherein determining metadata comprises determining whether one or more input fields contains input data. ### Claim 18 (depends on 17) The method of claim 17, wherein determining metadata comprises determining whether the input data of an input field comprises handwritten information. ### Claim 19 (depends on 12) The method of claim 12, further comprising classifying the one or more input fields. ### Claim 20 A non-transitory memory storing instructions that, when executed by at least one processor, cause a system to perform operations comprising: receiving a plurality of documents, individual documents of the plurality of documents having a same document type; generating a distribution of values for a pixel at a corresponding location in the individual documents of the plurality of documents; determining, based on the distribution, one or more common features of the plurality of documents; determining, based on a comparison of a pixel at the corresponding location in an individual document to the distribution, one or more input fields; generating a template including the one or more common features and the one or more input fields; and inputting synthetic data into the one or more input fields of the template thereby generating at least one of a plurality of synthetic documents.