Dynamic Threshold Background Removal for Image Processing
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Solution Overview
Problem
Existing background color removal processes in digital color copying machines are inefficient, especially in systems with limited storage capacity, leading to wastage of color materials and inaccurate reproduction due to the inability to distinguish between foreground and background effectively, particularly in documents with varying types and low background areas.
Innovation Solution
An image processing apparatus that determines count variation for each pixel based on its brightness, adjusting the threshold accordingly to differentiate between background and foreground, thereby enabling a stable background color removal process regardless of document type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a conventional background color removal process is used, then the processing can be executed in systems with limited storage capacity, but the foreground areas may be accidentally removed and image quality deteriorates
Solution Approach 1:
The patent applies dynamics by making the threshold variable rather than fixed. The threshold is dynamically adjusted based on the accumulated count variations of pixel brightness values. This allows the system to adapt to different document types and background characteristics, preventing foreground areas from being accidentally removed while maintaining the ability to effectively remove backgrounds in systems with limited storage capacity
Solution Approach 2:
The patent changes the parameter of threshold value from a static predetermined value to a dynamically adjusted value based on count variations. By accumulating count variations of pixel brightness and using this accumulated value to adjust the threshold, the system achieves more accurate background color removal that adapts to different document characteristics, resolving the contradiction between system simplicity and processing accuracy
2Productivity
If a fixed threshold is used for background color removal, then the processing is simple and fast, but it cannot adapt to different document types and may remove foreground areas
Solution Approach 1:
The patent transforms the fixed threshold into a dynamic threshold that adjusts based on accumulated count variations. This dynamic adjustment allows the system to maintain fast processing speeds while adapting to different document types, as the threshold modification is based on accumulated pixel data rather than requiring complex real-time analysis of each pixel
Solution Approach 2:
The patent implements feedback by using the accumulated count variations of pixel brightness values to adjust the threshold. This feedback mechanism allows the system to learn from the processed pixels and adapt the threshold accordingly, enabling the system to handle different document types effectively while maintaining processing efficiency through incremental adjustments
3Device complexity
If the background level is detected from the entire image, then the process is simple, but it fails when background area is small or foreground occupies most of the image
Solution Approach 1:
The patent applies local quality by determining count variation for each pixel individually based on its brightness value rather than treating the entire image uniformly. This per-pixel analysis allows the system to accurately identify background regions even when they occupy a small area, as each pixel's contribution to the accumulated count variation reflects its local characteristics
Solution Approach 2:
The patent uses partial action by accumulating count variations from pixels that meet specific criteria (brightness difference from threshold) rather than analyzing all pixels equally. This selective accumulation focuses computational effort on pixels that are likely to be background, improving detection accuracy for documents with small background areas while maintaining reasonable processing complexity
Data Source
AI summary
Input image data is converted into a brightness component to obtain a difference between the brightness component and a threshold. A count variation is determined based on the obtained difference, and the counter is used to follow up and change the threshold. The threshold obtained by the follow-up and change is used to execute a background color removal process in each pixel by executing a signal conversion process.