Target detection method with visible light and far infrared rays fused

Abstract

The invention discloses a target detection method with visible light and far infrared rays fused. The method comprises steps: an acquired visible image and an acquired far infrared thermal imaging image are blocked, and the obtained image blocks are converted to N*1 vectors; a mixed sampling matrix is constructed to carry out acquisition and compression on converted vectors to obtain each image block after compression; a pixel-level background modeling algorithm is adopted to detect each pixel point in each image block after compression, and a target area and a background area in the image block are determined; and the detected target image and the far infrared thermal imaging image are overlapped to obtain a target image after fusion. As the mixed sampling matrix is adopted to sample and compress the image, the calculation data amount is reduced, the learning rate is adjusted according to an area, the average calculation time is reduced, the pixel number is reduced on the whole, the background modeling time is effectively reduced, and compared with the traditional target detection algorithm, the target detection method of the invention enables the memory capacity to be reduced by three fourths and the processing time can be reduced by more than 40%.

Description

technical field [0001] The invention relates to the technical field of image detection, in particular to a target detection method that combines visible light and far infrared rays. Background technique [0002] In the application field of real-time vision system related to computer vision, the detection of the target in the acquired visual image is the first step. The quality of the target detection algorithm affects further visual processing such as follow-up tracking and behavior recognition. Due to the complexity and changeability of the actual scene, the existing target detection algorithms are generally complex, with a large amount of calculation and high memory capacity requirements, and are not suitable for real-time vision systems with limited resources. [0003] Therefore, the target detection algorithm for the real-time vision system must first consider the problem of algorithm efficiency, and reduce the amount of calculation and storage capacity as much as possi...

AI Technical Summary

Problems solved by technology

Due to the complexity and changeability of the actual scene, the existing target detection algorithms are generally complex, with a large amount of calculation and high memory capacity requirements, and are not suitable for real-time vision systems with limited resources.

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