Image Processing Apparatus Selective Grayscale Conversion
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Solution Overview
Problem
Conventional methods for converting color images to grayscale format often lose color information, leading to compromised discriminability and visibility issues, especially in images with overlapping colors or fine gradations, resulting in undesirable density steps and appearance in printed monochrome images.
Innovation Solution
An image processing apparatus that selectively targets objects for discriminability reproducing processing, excluding those that do not require improved discriminability, using processors and memories to convert color data into gray data based on specific criteria, such as adjacent graphics with similar colors, to prevent compromised appearances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If color conversion for all target colors is applied to convert RGB values into gray values using a uniform conversion scheme, then the tonality of color images is preserved in grayscale printing, but color information is lost and discriminability between different colors is compromised
Solution Approach 1:
The patent applies different conversion strategies to different regions or objects within the image. Objects with similar colors are identified and converted using NTSC conversion to preserve tonality, while objects requiring discriminability are converted using methods that maintain color differentiation. This local differentiation resolves the contradiction by applying the appropriate conversion method to each specific region rather than uniformly to the entire image.
2Loss of information
If discriminability reproducing processing is applied to all text and graphics in a page, then visibility and discriminability are improved, but density steps appear in reproduced images compromising appearance
Solution Approach 1:
The patent identifies specific objects or regions that require discriminability improvement and applies the processing only to those areas. By analyzing the image content and determining which objects benefit from enhanced discriminability, the system avoids applying density differences to all graphics, thereby preventing appearance degradation while maintaining visibility where needed.
Solution Approach 2:
Instead of applying discriminability reproducing processing to all elements in the image, the patent applies it partially only to specific objects that require it. This partial action approach avoids the excessive application that would cause density steps and appearance compromise, while still achieving the desired visibility improvement in critical areas.
3Loss of information
If density difference is provided to monochrome image based on number of colors and color values, then discriminability is improved with high visibility, but density steps are introduced in reproduced images
Solution Approach 1:
The patent applies density difference selectively to specific objects or regions rather than uniformly across the entire monochrome image. By identifying which objects require enhanced discriminability and applying density adjustments only to those areas, the system improves visibility where needed while avoiding the introduction of unwanted density steps in other regions, thus preserving overall image appearance quality.
Data Source
AI summary
An image processing apparatus for converting color data into gray data extracts an object included in the color data in a page, and determines, based on color information and position information on a first object and a second object extracted, whether at least one of the first object and the second object is to be a target of conversion of a color value of the color data into a gray value with improved discriminability. The image processing apparatus controls to convert the color value of the object into a gray value by a conversion targeting all color values, or into a gray value with the improved discriminability, based on the determination whether or not to be the target of conversion.