Image Processing Apparatus Paper Type Determination
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Solution Overview
Problem
Existing image processing technologies face challenges in accurately determining the type of paper originals, particularly due to differences in spectral characteristics and directional properties of fibers, leading to deviations in color reproducibility when scanning various types of papers.
Innovation Solution
An image processing apparatus and method that acquires spatial frequency features of paper fibers in read images to determine the original type, using two-dimensional DFT processing, binarization, and tetrahedron interpolation for accurate color conversion processing based on the type of paper.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional surface roughness and shape features are used for original type determination, then the determination process is simple, but determination accuracy deteriorates due to directional properties of fiber affecting run-length detection
Solution Approach 1:
The patent transitions from one-dimensional run-length analysis to two-dimensional spatial frequency analysis using DFT. By examining the frequency domain representation of the image, the system can identify fiber patterns regardless of their orientation in the spatial domain, thereby resolving the issue of directional properties affecting determination accuracy.
Solution Approach 2:
The patent replaces the mechanical/run-length based feature extraction method with a mathematical transformation approach (DFT). This substitution allows for more robust feature extraction that is not sensitive to the directional orientation of fibers, improving determination accuracy without significantly increasing system complexity.
2Reliability
If color conversion processing is performed using a single conversion table, then the processing is simple and fast, but color reproducibility deteriorates when scanning various types of originals with different spectral characteristics
Solution Approach 1:
The patent applies different color conversion tables based on the determined original type. By categorizing originals into different types (e.g., photographic sheet, printing sheet) and applying type-specific conversion tables, the system optimizes color reproducibility for each category while maintaining manageable processing complexity through the classification approach.
Solution Approach 2:
The patent changes the parameters of the color conversion process by selecting different conversion tables based on original type. This parameter change allows the system to adapt to different spectral characteristics of various original types, improving color reproducibility without requiring a completely complex adaptive system.
3Measurement precision
If run-length and number of times of change are used to detect period of irregularities, then the detection method is simple, but determination accuracy deteriorates when fiber direction causes unexpected variations in run-length
Solution Approach 1:
The patent transforms the detection problem from the spatial domain to the frequency domain using DFT. This dimensional change allows the system to detect periodic irregularities regardless of their orientation in the original image, eliminating the sensitivity to fiber direction that plagues run-length based methods while maintaining computational efficiency.
Data Source
AI summary
Because the spectral characteristics of an original of a printing sheet and those of an original of a photographic image are different, in the case where the same color conversion table is applied at the time of color conversion processing, a deviation occurs in color reproducibility. By determining the sheet type with accuracy based on the feature of fiber that occurs in manufacture of paper and by applying color conversion processing in accordance with the determination result, a highly accurate color reproduction method of an image is implemented.