Image Processing Apparatus Characteristic Point Preservation
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Solution Overview
Problem
Existing image processing technologies face challenges in reducing data amounts while preserving characteristic points, such as object contours, leading to potential loss of identifiable features during data reduction processing.
Innovation Solution
An information processing apparatus and method that acquires an input image, extracts characteristic point information, reduces the data amount of a secondary image, re-extracts characteristic point information from the reduced image, derives differences between the original and reduced characteristic point information, and corrects the reduced image accordingly to inhibit characteristic point loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data amount reduction processing is applied to images, then processing speed increases and memory usage decreases, but characteristic points such as object contours become lost
Solution Approach 1:
The patent extracts characteristic point information from the original image before data reduction processing is applied. This preliminary extraction ensures that important features are captured and preserved even when the image data is subsequently reduced, preventing loss of critical information while still achieving the benefits of data reduction for processing speed and memory efficiency
Solution Approach 2:
The patent compares characteristic point information extracted from the original image with characteristic point information extracted from the reduced image. By deriving the difference between these two sets of information, the system provides feedback to identify which characteristic points were lost during reduction, enabling corrective actions to restore or preserve these important features
Data Source
AI summary
In one aspect, an information processing apparatus includes a first acquisition module, a first extraction module, a first generation module, a second extraction module, a derivation module, and a first output control module. The first acquisition module acquires an input image to output a first image and a second image. The first extraction module extracts first characteristic point information from the first image. The first generation module generates a third image obtained by reducing a data amount of the second image. The second extraction module extracts second characteristic point information from the third image. The derivation module derives a difference between the first characteristic point information and the second characteristic point information. The first output control module outputs the third image corrected in accordance with the difference as an output image.