Document Image Extraction with Non-White Background Detection
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Solution Overview
Problem
Existing image processing systems face challenges in accurately extracting document images from a single scan when the background is not white, as they require strict operational conditions, such as using a black backing sheet placed correctly, which can lead to errors if not followed correctly by the operator.
Innovation Solution
An image processing apparatus with a first detection unit for rectangular shapes and a second detection unit that identifies rectangular shapes within detected shapes as document images, even when the background is not white, by using a combination of modules for image reduction, shape detection, and condition determination to enhance the precision of document image extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a black backing sheet is used to improve document image extraction accuracy, then extraction precision is improved, but operational complexity increases and errors occur when not placed correctly
Solution Approach 1:
The system performs self-diagnosis by automatically detecting whether a backing sheet is present and determining the background color. The detection unit analyzes the image to identify backing sheet characteristics, eliminating the need for operator intervention in placing or configuring the backing sheet correctly.
Solution Approach 2:
The system dynamically adjusts processing parameters based on detected background color. When a non-white background is detected, the image processing parameters are automatically modified to compensate, allowing accurate document extraction regardless of whether a black backing sheet is used or misplaced.
2Reliability
If strict operational conditions are imposed to ensure accurate extraction, then extraction reliability is improved, but device complexity and operational difficulty increase
Solution Approach 1:
The detection unit provides feedback about the scanning environment (presence of backing sheet, background color) to the image processing unit. This feedback loop allows the system to automatically adapt processing parameters to maintain reliable extraction without requiring complex operational conditions or user expertise.
Solution Approach 2:
The detection unit acts as an intermediary between the scanning environment and the image processing unit. It automatically identifies and characterizes the backing sheet and background conditions, translating environmental variations into processed information that guides subsequent extraction operations without requiring direct user intervention.
3Measurement precision
If manual placement of black backing sheet is required to achieve accurate results, then extraction precision is improved, but loss of time occurs due to operator errors and rework
Solution Approach 1:
The system performs preliminary detection of the scanning environment before document extraction. By automatically identifying the presence and characteristics of any backing sheet in advance, the system prepares appropriate processing parameters proactively, eliminating the need for manual placement and subsequent correction if errors occur.
Solution Approach 2:
The system autonomously handles the entire process from environment detection to parameter adjustment without requiring operator intervention for backing sheet placement or configuration. This self-service capability eliminates time losses associated with manual operations and their potential errors.
Data Source
AI summary
An image processing apparatus includes a first detection unit and a second detection unit. The first detection unit detects a rectangular shape in an image including plural document images. The second detection unit detects, in a case where a background of the rectangular shape is not white, rectangular shapes included in the rectangular shape detected by the first detection unit as document images.