Image Processing Gradation Control for Mixed-Attribute Documents
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Solution Overview
Problem
Existing image processing methods, such as those described in Japanese Unexamined Patent Application Publication No. 2007-266921, often result in significant information loss when processing documents with mixed attributes, as they inadequately determine the appropriate scanning method for text data with halftone-color backgrounds, leading to illegible characters.
Innovation Solution
An image processing apparatus that calculates a feature value from input image data to accurately set the number of output gradations, using a feature-value calculating unit, an output-gradation-number setting unit, and an image processor to generate output image data with appropriate gradations, thereby minimizing information loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the scanning method is switched based on document attribute classification (color/monochrome, text/photograph), then processing efficiency is improved, but information loss increases when dealing with mixed-attribute documents
Solution Approach 1:
The patent applies local quality by evaluating different regions of the document image independently. The image is divided into multiple blocks, and each block is assessed for its information loss risk when converted to binary data. This allows different processing decisions to be made for different regions, preserving text legibility in critical areas while maintaining overall processing efficiency.
Solution Approach 2:
The patent changes parameters by introducing quantitative evaluation metrics (feature values) to determine the appropriate output format. Instead of relying on simple classification, the system calculates feature values such as text density, background complexity, and character contrast to dynamically adjust the processing approach for each document region.
2Quantity of substance
If binary data processing is applied to text documents, then data compression is improved, but character legibility deteriorates when backgrounds are halftone-color
Solution Approach 1:
The patent evaluates each block of the document image to determine whether it should be converted to binary data or retained in gray-scale. By analyzing local characteristics such as text density and background complexity, the system preserves binary data compression benefits in suitable regions while protecting character legibility in regions where binary conversion would cause information loss.
Solution Approach 2:
The patent introduces a feedback mechanism where feature values are calculated from the original image, used to determine the appropriate processing mode, and then the results are evaluated. This feedback loop ensures that binary conversion is only applied when it will not compromise character legibility, allowing the system to adaptively optimize both compression and readability.
3Ease of operation
If automatic document feeding is used to reduce user burden, then ease of operation is improved, but document attribute recognition accuracy deteriorates due to mixed-attribute sets
Solution Approach 1:
The patent segments the document image into multiple blocks for independent evaluation. This segmentation allows the system to handle mixed-attribute documents by processing each block according to its specific characteristics, overcoming the limitation of treating the entire document as a single uniform type.
Solution Approach 2:
The patent changes from qualitative document classification to quantitative feature value evaluation. By calculating numerical features such as text density, background complexity, and character contrast for each block, the system achieves more precise attribute recognition that can handle the complexity of mixed-attribute documents fed automatically.
Data Source
AI summary
An image processing apparatus processes input image data and generates output image data. The image processing apparatus includes a feature-value calculating unit, an output-gradation-number setting unit, and an image processor. The feature-value calculating unit calculates a feature value from the input image data. The output-gradation-number setting unit sets, as the number of output gradations, any one gradation number of candidates for the number of output gradations based on the feature value calculated by the feature-value calculating unit. The image processor processes the input image data and generates the output image data having the number of output gradations which is set by the output-gradation-number setting unit.