Image Processing Device Selecting Color Component for Text Binarization
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Solution Overview
Problem
Conventional image processing technologies fail to generate suitable binary image data for rendering text from image data, as they do not adequately consider setting threshold values during the thresholding process.
Innovation Solution
An image processing device and method that identifies background and letter color values in a color coordinate system, calculates differences between these values, selects a specific component with the maximum difference, and performs a binarizing process on that component to generate binary image data, effectively setting a threshold value based on text sharpness to produce clear text binary data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional thresholding process is used without considering threshold value settings, then processing is simple, but text rendering quality deteriorates
Solution Approach 1:
The patent changes the parameter of threshold values by calculating component differences between background and letter colors, and selecting appropriate threshold values based on these differences. This resolves the contradiction by automatically determining optimal threshold values that maintain text rendering quality while keeping the process systematic and manageable.
Solution Approach 2:
The patent segments the color information into multiple components (R, G, B) and processes each component separately by calculating differences between background and letter colors. This segmentation allows for precise control of text rendering quality in each color channel while maintaining overall processing efficiency.
2Productivity
If threshold values are not properly set, then processing is fast, but text sharpness deteriorates
Solution Approach 1:
The patent performs preliminary calculations of component differences between background and letter colors before the actual thresholding process. This preliminary action establishes the foundation for selecting appropriate threshold values, ensuring text sharpness is maintained while keeping the subsequent binarization process fast and efficient.
Solution Approach 2:
The patent dynamically adjusts threshold values based on calculated component differences, changing the threshold parameter according to the specific image characteristics. This ensures optimal text sharpness is achieved while maintaining processing speed through automated parameter selection.
3Device complexity
If binary image data is generated without component selection, then processing is simple, but text element thickness becomes inconsistent
Solution Approach 1:
The patent applies local quality by selecting specific color components (R, G, or B) based on which component shows the maximum difference between background and letter colors. This local optimization ensures that each text element is processed using the most appropriate color channel, maintaining consistent text element thickness while keeping the overall approach systematic rather than overly complex.
Data Source
AI summary
An image processing device includes a processor configured to perform: acquiring target image data representing a target image; and generating binary image data representing the letter in the target image by using the target image data. The generating of the binary image data comprises: identifying a background color value representing color of background of the target image; identifying a letter color value representing color of the letter in the target image; acquiring a difference between the background color value and the letter color value, the difference including a plurality of component differences; selecting one specific component image data corresponding to a specific component from among the plurality of components, the specific component corresponding to a maximum component difference among the plurality of component differences; and performing a binarizing process on the selected one specific component image data to generate one binary image data.