Object Edge Detection via Vertex Recognition and Corner Point Analysis
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Solution Overview
Problem
Existing digital image processing methods struggle to accurately detect and extract object edges from images, especially when the object is surrounded by redundant external environment information.
Innovation Solution
A method and system that utilize an object vertex recognition model to identify object vertices and their relative positions within an image, followed by corner point detection to determine the actual positions of these vertices, and finally connect adjacent vertices to form edge lines, thereby extracting the object edges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional edge detection methods are used, then the processing is simple and fast, but the detection accuracy is low when objects are surrounded by redundant external environment information
Solution Approach 1:
The patent segments the edge detection process into multiple distinct stages: vertex recognition model processing, corner point detection in predetermined areas, and edge line formation by connecting vertices. This segmentation allows each stage to focus on specific tasks, improving overall detection accuracy while maintaining organized processing flow
Solution Approach 2:
The patent performs preliminary actions by first identifying object vertices through a recognition model and determining their reference positions before conducting corner point detection. This preliminary vertex identification guides the subsequent corner point detection process, ensuring that detection efforts are concentrated on relevant areas, thereby improving accuracy without proportionally increasing complexity
2Measurement precision
If corner point detection is performed in predetermined areas for each object vertex, then the edge detection accuracy is improved, but the processing time increases
Solution Approach 1:
The patent applies local quality by performing corner point detection only in predetermined areas surrounding identified object vertices, rather than processing the entire image. This localized approach concentrates computational resources on critical regions, improving vertex position accuracy while minimizing unnecessary processing time consumption in irrelevant areas
Solution Approach 2:
The patent employs partial action by conducting corner point detection only in predetermined areas around vertices rather than exhaustive full-image processing. This partial approach achieves sufficient accuracy for edge detection without the time cost of complete image analysis, balancing precision and efficiency
3Measurement precision
If machine learning models are used for vertex recognition, then the recognition accuracy is improved, but the computational resources required increase
Solution Approach 1:
The patent segments the computational workload by separating vertex recognition (handled by the machine learning model) from corner point detection and edge formation (handled by traditional image processing). This segmentation allows the energy-intensive ML model to focus only on vertex identification, while simpler algorithms handle subsequent processing, optimizing overall energy consumption
Solution Approach 2:
The patent uses the vertex recognition model to perform preliminary identification of object vertices before conducting corner point detection. This preliminary action by the ML model provides accurate vertex locations that guide subsequent processing, ensuring high recognition accuracy while allowing later stages to operate more efficiently with targeted processing
Data Source
AI summary
A method and system of recognizing object edges and a computer-readable storage medium are provided. The method includes: obtaining an input image; recognizing the input image and obtaining a relative position of each object vertex and a corresponding image vertex thereof; determining a reference position of each object vertex in the input image according to the relative position of each object vertex and the corresponding image vertex thereof; performing corner point detection in a predetermined area where the reference position of the object vertex is located for each object vertex; determining an actual position of each object vertex in the input image according to a result of the corner point detection; and sequentially connecting adjacent object vertices to form edge lines to obtain the edges of the object with edges in the input image according to the actual position of each object vertex in the input image.