Image Processing Apparatus Automatic Correction Selection
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Solution Overview
Problem
Users face difficulties in selecting appropriate correction processing for image data generated by optically reading documents, as existing technologies do not provide a straightforward method to determine the suitable processing type and parameter settings, leading to user burden and increased trouble.
Innovation Solution
An image processing apparatus that calculates index values based on the color distribution of original and corrected images to determine the corresponding correction processing among multiple candidates, allowing for automatic execution and reduced user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple types of correction processing are provided to users, then the versatility and adaptability of the image processing apparatus is improved, but the ease of operation deteriorates because users cannot easily select the appropriate processing from many options
Solution Approach 1:
The system automatically determines the appropriate correction processing by analyzing color distribution differences between original and corrected images, eliminating the need for users to manually select from multiple processing options. The apparatus performs self-diagnosis of the correction type based on objective color metrics
Solution Approach 2:
The system uses color distribution parameters (color histograms, color moments) as objective criteria to identify and classify different correction processing types. By monitoring changes in these parameters before and after correction, the system can automatically determine which processing was applied
2Ease of operation
If automatic determination of correction processing is implemented, then the ease of operation is improved, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The system replaces manual user judgment and selection with automated computational analysis of color distribution data. Instead of relying on user expertise to identify correction types, the system uses algorithmic processing of color histograms and color moments to objectively determine the correction processing applied
3Measurement precision
If color distribution analysis is used to determine correction processing, then the measurement precision is improved, but the loss of time increases due to additional calculation steps
Solution Approach 1:
The system pre-calculates and stores color distribution data (histograms, color moments) for various correction processing types during system initialization or setup. When determining the applied correction, the system compares current image data against these pre-computed references, significantly reducing the time required for real-time determination
Data Source
AI summary
An image processing apparatus includes: a controller configured to perform: acquiring original image data representing an original image and corrected image data representing a corrected image, the corrected image data being generated by executing specific correction processing on the original image data; calculating a first index value and a second index value, the first index value relating to a color distribution of the original image by using the original image data, and the second index value relating to a color distribution of the corrected image by using the corrected image data; and determining which processing, among a plurality of processing candidates that are executable by the image processing apparatus, corresponds to the specific correction processing, based on comparison of the calculated first index value and the calculated second index value.