Automated Form Definition Generation via OCR and Image Processing
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Solution Overview
Problem
Manual definition of form content and layout when switching from one enterprise resource planning (ERP) system to another is a tedious, time-consuming, and error-prone process, especially for organizations using many complex forms.
Innovation Solution
Automated generation of form definitions by processing captured images of hard-copy forms using optical character recognition (OCR) to identify form fields, determine geometrical coordinates, and associate field names with data objects, thereby creating a form definition that can be used in the new ERP system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual definition of form content and layout is performed, then form definition can be accurately created, but the process is tedious, time-consuming, and error-prone
Solution Approach 1:
The patent uses optical character recognition (OCR) to copy text content from hard-copy form images and automatically extracts form field information, replacing the manual copying and definition process. This allows accurate form definition generation without manual intervention in the data extraction phase.
Solution Approach 2:
The patent replaces manual mechanical processes of form definition creation with automated computer-based processing. The system automatically processes form images, identifies fields, extracts text, and generates form definitions through computational algorithms rather than manual operations.
2Manufacturing precision
If manual definition of form content and layout is performed, then form definition can be accurately created, but the process is tedious and error-prone
Solution Approach 1:
The system performs self-service by automatically processing form images and generating form definitions without requiring manual intervention. The automated process independently identifies form fields, extracts text characters, determines geometrical coordinates, and creates form definitions, eliminating the need for manual operation.
Solution Approach 2:
The patent replaces manual mechanical processes of form definition creation with automated computer-based processing. The system automatically processes form images, identifies fields, extracts text, and generates form definitions through computational algorithms rather than manual operations.
3Productivity
If automated processing of form images is performed, then form definition generation time is reduced, but the complexity of the processing system increases
Solution Approach 1:
The patent segments the form processing task into distinct functional modules: image capture, optical character recognition, form field identification, geometrical coordinate determination, and form definition generation. This segmentation allows each component to handle a specific aspect of processing independently, making the overall complex system manageable and maintainable.
Solution Approach 2:
The patent uses an intermediary processing layer that bridges the hard-copy form images and the digital form definition requirements. The automated processing system acts as an intermediary that translates physical form images into structured digital form definitions through standardized processing steps.
4Productivity
If automated processing of form images is performed, then form definition generation speed is improved, but the complexity of the processing system increases
Solution Approach 1:
The patent creates a universal processing system that can handle various form types and layouts through a single automated framework. The system uses general-purpose algorithms for image processing, OCR, and field identification that can be applied across different form formats, eliminating the need for separate specialized systems for each form type.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces human involvement and time required for form definition, minimizing errors by leveraging existing hard-copy forms to define equivalent forms in the new ERP system, enabling efficient filling and printing of forms.
Implementation Method 1
Optical character recognition (OCR) is applied to the text characters in order to identify form field names
Data Source
AI summary
A computer-implemented method for form generation includes capturing an image of a hard-copy form, and automatically processing the image to identify form fields in the image and text characters associated with each of the form fields. Geometrical coordinates of the form fields that define respective filling areas for entry of information into the fields are determined. Optical character recognition (OCR) is applied to the text characters in order to identify form field names. Associations are determined between the form field names and object names of corresponding data objects. The geometrical coordinates of the filling areas of the form fields are combined with the object names of the data objects corresponding to the form fields to generate a form definition.