Stamp Detection in Scanned Documents Using Sequential Shape Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated document processing systems face challenges in accurately detecting stamps due to their varying sizes, placements, shapes, and colors, which can obscure text and hinder optical character recognition (OCR), requiring efficient methods to minimize human error and resource usage.
Innovation Solution
A sequential computerized algorithmic method that detects regular shapes in images, removes text and noise, and inscribes or encloses remaining shapes to identify stamps, using edge detection, contour calculation, and shape comparison, with optional color filtering and template matching, to classify documents as stamped or not.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine learning/AI techniques are used for stamp detection, then detection accuracy may improve, but large set of training data is required and system complexity increases
Solution Approach 1:
The patent replaces complex machine learning/AI systems with a simpler rule-based image processing system. The method uses sequential algorithmic steps including edge detection, contour calculation, shape classification, and color analysis to detect stamps without requiring training data or complex neural networks, thereby reducing system complexity while maintaining detection accuracy
Solution Approach 2:
The patent changes the approach from learning-based parameter adjustment to fixed parameter-based detection. By using predetermined shape criteria (circles, ellipses, rectangles, triangles), color thresholds, and size ranges, the system achieves reliable stamp detection through explicit parameter specifications rather than learned parameters, eliminating the need for large training datasets
2Device complexity
If traditional image processing methods are used for stamp detection, then system complexity is reduced, but detection accuracy deteriorates due to varying stamp characteristics
Solution Approach 1:
The patent segments the stamp detection problem into distinct sequential steps: edge detection to identify boundaries, contour calculation to define shapes, shape classification to categorize regular vs. irregular forms, and color analysis to identify stamp regions. This segmentation allows each step to be handled with simple, well-defined operations that collectively achieve high detection accuracy across varied stamp characteristics
Solution Approach 2:
The patent adds color space analysis (HSV color model) as an additional dimension to shape-based detection. By analyzing hue, saturation, and value parameters alongside geometric properties, the system can distinguish stamps from other document elements even when shapes are irregular, thereby improving detection accuracy without significantly increasing system complexity
3Reliability
If stamps are detected in documents, then document authentication is enabled, but text obscuration occurs preventing complete OCR
Solution Approach 1:
The patent extracts stamp regions from the document image through precise detection and segmentation. By identifying stamp boundaries using edge detection, contour analysis, and shape classification, the system isolates stamp areas so that subsequent OCR processing can focus on non-stamp regions, preventing text information loss while maintaining document authentication capability
Data Source
AI summary
Systems and methods for detecting stamps include if at least one regular shape in an image of a document is detected then outputting said at least one regular shape as a stamp; else: removing at least one of text, lines, and noise in the image of the document; and if at least one closed shape is remaining in the image of the document, then inscribing said at least one closed shape and outputting said at least one inscribed closed shape as a stamp; else if at least one open shape is remaining in the image of the document, then enclosing said at least one open shape and outputting said at least one enclosed shape as a stamp.