Scanned Image Binarization for Eraser Trace Removal
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Solution Overview
Problem
Existing image processing systems that darken character areas for correction also darken unnecessary areas such as eraser traces, making it difficult to distinguish between necessary and unnecessary parts of a scanned image.
Innovation Solution
An image processing apparatus that calculates a density value histogram, sets a threshold value based on the most frequently appearing density value, and performs binarization to correct areas above the threshold to black and below to white, effectively removing unnecessary areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the character area of the scanned image is made darker for correction, then the grader can easily recognize characters written in answer fields, but unnecessary areas such as eraser traces are also made darker
Solution Approach 1:
The patent applies different density correction levels to different areas of the scanned image based on their characteristics. Character areas receive darker correction to enhance visibility, while eraser trace areas are identified and excluded from darkening through histogram analysis and threshold-based segmentation. This local differentiation resolves the contradiction by making correction selective rather than uniform across the entire image.
Solution Approach 2:
The patent applies density correction only to specific portions of the image that meet certain criteria rather than uniformly to the entire image. By using histogram analysis to identify character density ranges and applying correction only within those ranges, the system performs partial action on the image data, correcting character areas while leaving eraser traces unaffected.
2Measurement precision
If density correction is applied to enhance character visibility, then grading accuracy improves, but distinction between necessary and unnecessary areas deteriorates
Solution Approach 1:
The patent performs preliminary histogram analysis and threshold determination before applying density correction. By pre-identifying the density characteristics of character areas versus eraser trace areas through histogram computation, the system establishes correction parameters in advance that preserve area distinction information while enhancing character visibility for accurate grading.
Data Source
AI summary
An image processing apparatus capable of removing an unnecessary area from a scanned image and thereby making it easy to recognize a necessary area of the scanned image. The image processing apparatus includes a calculation unit that calculates a density value histogram based on an acquired scanned image, a setting unit that sets a necessary area density that has a predetermined value range around the most frequently appearing density value having the highest appearance frequency in the density value histogram, and sets a binarization threshold value based on the necessary area density, and a control unit that controls execution of binarization processing for correcting an area of the scanned image, in which density values are equal to or higher than the threshold value, to black, and correcting an area of the scanned image, in which density values are lower than the threshold value, to white.