Target detection method and apparatus
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Solution Overview
Problem
Existing target detection methods, such as those using the hybrid Gaussian algorithm, are complex and require significant computational resources, making them inefficient for simple and effective target detection in target scenes.
Innovation Solution
A target detection method that uses an image acquiring device to capture images of a region illuminated by light sources with different angles, determining the presence of a target based on significant gray scale differences between images, as shadows formed by the target create distinct gray scale variations when light sources with different angles are used.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the hybrid Gaussian algorithm is used to detect whether a target exists in the target scene, then the detection accuracy can be maintained, but the amount of calculation becomes large and complex
Solution Approach 1:
The patent extracts only the essential feature for target detection - the gray scale difference caused by shadows - from the complex hybrid Gaussian algorithm. By using multiple light sources at different angles to create shadows and comparing gray scale values, the method isolates the critical detection mechanism while eliminating unnecessary computational complexity, thus resolving the contradiction between detection accuracy and calculation complexity
Solution Approach 2:
The patent replaces the complex mathematical modeling and continuous model updating of the hybrid Gaussian algorithm with a simpler optical-mechanical approach using multiple light sources at different angles. This substitution uses physical shadow formation and gray scale comparison instead of complex iterative calculations, maintaining detection effectiveness while significantly reducing computational burden
2Reliability
If the hybrid Gaussian algorithm is used to detect whether a target exists in the target scene, then the detection function can be achieved, but the detection process becomes complex and not simple enough
Solution Approach 1:
The patent segments the detection process into distinct, simple steps: illuminating the target scene with multiple light sources at different angles, acquiring images with an image acquiring device, and comparing gray scale differences. This segmentation breaks down the complex hybrid Gaussian algorithm into elementary operations that are easier to implement and understand, while maintaining the essential detection function
Solution Approach 2:
The patent changes the detection parameter from complex model-based metrics to simple gray scale differences. By using multiple light sources at different angles to create varying shadow patterns and comparing the resulting gray scale values in acquired images, the method simplifies the detection parameter while preserving the ability to reliably detect target presence
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach simplifies the target detection process by leveraging gray scale differences to effectively identify targets of various sizes, including both larger and smaller targets, without the need for complex model updates or extensive calculations.
Implementation Method 1
when a target exists in the region to be detected and light sources with different illuminating angles illuminate the region to be detected, the target may form shadows of different angles in the region to be detected
Data Source
Figure 1~2B
Figure 3~4A
Figure 4B~6
AI summary
The embodiments of the present application provides a target detection method, which comprises: obtaining a plurality of images acquired by an image acquiring device as images to be detected when a region to be detected is illuminated by light sources with different illuminating angles, wherein the different illuminating angles correspond to the different images to be detected(S101); and determining whether a target exists in the region to be detected based on gray scale differences between the obtained images to be detected with illuminating by the light sources of with different illuminating angles(S 102). The method is applied to achieve a simple and effective detection of the target existing in the region to be detected.