Image Detection via Edge-Straitline Geometry Analysis
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Solution Overview
Problem
Current image detection systems face challenges in quickly and accurately identifying target objects from large volumes of data, especially when cameras have different specifications and capture varying angles and directions, making it difficult to search for vehicles and other moving objects.
Innovation Solution
An image detecting method and system that captures original images, creates moving-object images and edge-straight-line images, and detects mechanical moving objects based on the length, parallelism, and gap of edge-straight-lines, increasing detection speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional image detection methods are used, then the system can process images, but the detection speed is slow and accuracy is low when dealing with large volumes of data from multiple cameras with different specifications and angles
Solution Approach 1:
The patent segments the image detection process into multiple independent stages: image acquisition, edge detection, straight line extraction, parallelism analysis, and object identification. Each stage processes specific features separately, allowing efficient handling of large volumes of data while maintaining high accuracy through focused analysis at each step.
Solution Approach 2:
The patent transforms the detection problem from analyzing complete images to analyzing extracted edge-straight-lines in a simplified feature space. By converting complex image data into geometric features (length, parallelism, gap of edge-straight-lines), the system achieves faster processing while maintaining identification accuracy.
2Measurement precision
If the system analyzes complete images to identify objects, then detection can be performed, but the process becomes time-consuming when dealing with large volumes of data
Solution Approach 1:
The patent extracts only the essential geometric features (edge-straight-lines with specific length, parallelism, and gap characteristics) from complete images. This extraction approach allows the system to maintain accurate object identification while significantly reducing detection time by analyzing only the extracted features rather than processing entire images.
Solution Approach 2:
The patent performs preliminary edge detection and straight line extraction before the actual object identification. This preliminary action simplifies the data structure and prepares essential features in advance, enabling faster and more accurate object identification from the extracted edge-straight-lines.
3Adaptability or versatility
If the system handles multiple cameras with different specifications and capture angles, then comprehensive coverage is achieved, but the complexity of searching and identifying objects increases
Solution Approach 1:
The patent creates a universal detection algorithm that works across multiple cameras with different specifications and capture angles. By extracting geometric features (edge-straight-lines) that are invariant to camera parameters, the same detection process can handle diverse camera configurations without increasing system complexity.
Solution Approach 2:
The patent transforms the detection approach by changing from camera-parameter-dependent image analysis to geometric-feature-based analysis. The edge-straight-lines are extracted and analyzed based on their intrinsic geometric properties (length, parallelism, gap) rather than camera-specific parameters, making the system adaptable to multiple camera configurations while maintaining consistent detection complexity.
Data Source
AI summary
An image detecting method and a system thereof are provided. The image detecting method includes the following steps. An original image is captured. A moving-object image of the original image is created. An edge-straight-line image of the original image is created, wherein the edge-straight-line image comprises a plurality of edge-straight-lines. Whether the original image has a mechanical moving-object image is detected according to the length, the parallelism and the gap of the part of the edge-straight-lines corresponding to the moving-object image.