Adaptive Contrast Control via Local Black and White Point Segmentation
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Solution Overview
Problem
Existing methods for enhancing digital documents, such as thresholding, leveling, and brightness/contrast adjustments, are inadequate in improving readability and compressibility, especially for documents with varying contrast and quality issues, and are often computationally expensive or ineffective in real-time applications.
Innovation Solution
The method involves partitioning a document image into non-overlapping areas, determining local black and white point values for each area, and calculating revised pixel grayscale values using these values and those from adjacent areas, allowing for adaptive contrast control without pixel-by-pixel analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If adaptive thresholding is used to improve document readability, then contrast is improved, but computational cost increases significantly
Solution Approach 1:
The patent divides the document image into multiple non-overlapping areas and processes each area independently to determine local black and white point values. This segmentation allows adaptive contrast control without requiring computationally expensive pixel-by-pixel analysis across the entire image, thus improving readability while maintaining processing efficiency.
Solution Approach 2:
The patent applies different black and white point values to different areas of the document based on local characteristics. By determining area-specific threshold values rather than using a global threshold, the system adapts to local variations in document quality and lighting conditions, improving overall readability without excessive computational cost.
2Manufacturing precision
If global leveling is applied to improve overall document contrast, then some areas are improved, but local variations are not addressed and effect is reduced
Solution Approach 1:
The patent segments the document into multiple areas and determines black and white point values for each area independently. This allows the system to address local variations in contrast while maintaining overall document improvement, overcoming the limitation of global leveling that treats the entire image uniformly.
Solution Approach 2:
By assigning different black and white point values to different areas based on their local characteristics, the patent enables each area to be optimized independently. This local adaptation ensures that areas with different lighting conditions, document quality, or content types receive appropriate contrast adjustment, improving both overall and local document quality.
3Measurement precision
If pixel-by-pixel analysis is performed to achieve optimal contrast, then precision is maximized, but computational complexity and processing time increase
Solution Approach 1:
The patent reduces computational complexity by dividing the image into areas and processing each area as a unit rather than analyzing each pixel individually. This segmentation maintains sufficient precision for contrast control while dramatically reducing the computational burden compared to true pixel-by-pixel analysis.
Solution Approach 2:
The patent applies partial action by determining black and white point values for areas rather than for every pixel. This approach provides sufficient contrast precision for practical purposes without the excessive computational cost of complete pixel-level analysis, achieving an optimal balance between precision and complexity.
4Quantity of substance
If thresholding is used to improve compressibility, then file size is reduced, but readability may be compromised
Solution Approach 1:
The patent applies local black and white point values to different areas before converting to bitonal format. This area-specific thresholding ensures that each region is optimized for both compressibility and readability, maintaining text clarity while achieving effective compression. The local adaptation prevents the loss of readability that can occur with global thresholding methods.
Data Source
AI summary
A method of operating on an image of a document includes, for an electronic file that includes a representation of the document, portioning the representation of the document into non-overlapping areas. Each area includes a matrix of pixels and each pixel has an initial grayscale value and a position in the matrix. The method also includes, for each area, determining a black point value and a white point value. The method further includes, for each pixel in each area, determining a revised pixel grayscale value for the pixel using the pixel's grayscale value, the pixel's position in the matrix, the black point value for the area comprising the pixel, the white point value for the area comprising the pixel, the black point value for at least one area adjacent to the area comprising the pixel, and/or the white point value for at least one area adjacent to the area comprising the pixel. The method also includes producing the image of the document using the revised grayscale values for each pixel.