A target detection method, device and computer-readable storage medium

Abstract

The invention discloses a target detection method, equipment and computer-readable storage medium. Through the fusion of infrared light and visible light images, and comparing and matching the shape template with the contour information of the object to be detected, it is determined that the matching similarity is satisfied. The outline information of the condition is a set of target information, which solves the problem that in actual scenes, objects that are similar to the shape of the target to be detected but not the target to be detected often appear, for example, when the image to be detected is a certain traffic road image, the object to be detected When the target is a pedestrian, there may be street lights, trees, etc. similar to pedestrians on the traffic road image, resulting in inaccurate target detection results.

Description

Technical field [0001] The present invention relates to image detection, and more particularly to a target detection method, a device, and a computer readable storage medium. Background technique [0002] Target detection technology, also called target extraction, is an image segmentation based on target geometry and statistical characteristics, segmentation and identification of the target, can identify the target to be detected in the image to be detected, in videos Surveillance, public security, automatic driving, biomedical, etc. have a wide range of applications, more generally, standing to detect images for a traffic road image, when the target is for pedestrians, target detection technology can put traffic road images Pedestrian information identifies. [0003] In the actual implementation process, it is found that in the actual scenario, since there are often objects to be detected due to similar to the target, it is not the target to be detected, for example, the detecte...

AI Technical Summary

Problems solved by technology

[0004] The object detection method provided by the present invention solves the problem that objects that are similar to the target to be detected but not the target to be detected often appear in the actual scene. For example, when the image to be detected is a certain traffic road image, the target to be detected When it is a pedestrian, there may be street lights, trees, etc. similar to pedestrians on the traffic road image, resulting in inaccurate target detection results.

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