Image Processing Apparatus for Used Car Part Defect Detection
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Solution Overview
Problem
The process of identifying defects in used car parts is time-consuming and subjective, leading to inefficiencies and inaccuracies in defect identification and recording, which hinders the recycling and trading of these parts.
Innovation Solution
An image processing apparatus and method that detects defects in used car parts from images using an image analysis model, such as a U-Net neural network, to objectively determine defect types and sizes, reducing the reliance on human judgment and enhancing inspection reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If workers visually inspect used car parts to identify defects, then defect identification can be performed, but the process takes a very long time and is subjective
Solution Approach 1:
The patent replaces the mechanical visual inspection system with an image processing system that uses cameras to capture images of car parts and algorithms to automatically detect and measure defects. This substitution eliminates the need for human workers to visually inspect parts, thereby reducing inspection time while maintaining or improving reliability through objective digital analysis.
Solution Approach 2:
The patent creates digital copies (images) of the car parts instead of requiring physical visual inspection by workers. These image copies are then processed by computer algorithms to identify defects, allowing for rapid analysis without the time constraints and subjectivity of human inspection while maintaining accurate defect detection.
2Measurement precision
If workers manually record defect information, then defect data can be collected, but errors occur in handwritten records and subjective judgment affects accuracy
Solution Approach 1:
The patent replaces manual handwritten recording with automated digital data capture and processing. The system automatically measures defect characteristics from images and stores the data digitally, eliminating transcription errors and ensuring accurate, objective recording of defect information without the subjectivity inherent in human judgment.
Solution Approach 2:
The system performs self-service by automatically detecting, measuring, and recording defect information without requiring human intervention for data entry or judgment. The image processing algorithm independently analyzes the images and generates accurate defect records, eliminating errors associated with manual recording and subjective human assessment.
3Productivity
If automatic image analysis is implemented, then inspection speed increases and objectivity improves, but device complexity increases
Solution Approach 1:
The patent segments the image processing system into distinct functional modules: image capture module, defect detection module, measurement module, and data recording module. This segmentation allows each component to perform its specific function independently, making the overall complex system more manageable and easier to implement while maintaining high productivity and objectivity in the inspection process.
Data Source
AI summary
In an embodiment, an image processing apparatus can include a memory storing computer-executable code, and at least one processor configured to access the memory and execute the instructions. The code comprises instructions for the at least one processor to generate an input image by preprocessing an image around a part, based on detecting the part from the image, apply the input image to an image analysis model to obtain a defect type and a defect size of the part detected from the image, and apply the defect type and the defect size to the input image to generate an output image.