Image Processing Apparatus Abnormality Detection via Homography
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for determining abnormalities in objects, such as label sheets on products, are inefficient and lack precision in identifying defects.
Innovation Solution
A computer-based system that captures images of the object's surface, performs keypoint matching between the captured image and a normal image, and applies homography transformation to generate a transformed image, allowing for accurate abnormality determination by comparing the transformed image with the original.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine learning models are used to determine abnormalities in objects, then abnormality detection capability is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs homography transformation preliminarily to generate a transformed image that corrects perspective distortion before abnormality detection. This preliminary geometric correction eliminates the need for complex machine learning models to compensate for perspective effects, thereby reducing processing time while maintaining detection accuracy
Solution Approach 2:
The patent extracts and corrects only the perspective distortion component from the captured image using homography transformation, separating this geometric correction step from the subsequent abnormality detection process. This extraction allows simple comparison-based detection methods to be used instead of comprehensive machine learning approaches
2Productivity
If captured images are directly compared with normal images for abnormality detection, then processing speed is improved, but detection accuracy deteriorates due to projection plane differences
Solution Approach 1:
The patent introduces a transformed image as an intermediary between the captured image and the normal image for comparison. This intermediate step performs homography transformation to align the projection planes, enabling accurate comparison while maintaining processing efficiency through simple image transformation and comparison operations
Data Source
AI summary
A set of program instructions, when executed by a processor of a computer, causes the computer to perform: acquiring a two-dimensional captured image of a particular surface of a target object; keypoint matching between the two-dimensional captured image and a two-dimensional normal image representing a normal particular surface; generating a transformed image by performing homography transformation on a first image in accordance with a result of the keypoint matching, the first image being one of the two-dimensional captured image and the two-dimensional normal image; and determining whether the particular surface of the target object has an abnormality by comparing a second image with the transformed image, the second image being an other one of the two-dimensional captured image and the two-dimensional normal image.