Abandoned object detection method

Abstract

The invention discloses an abandoned object detection method. Brand-new environment self-adaptation double background models are built, and the background models are a front background model and a back background model respectively; independent update mechanisms are set for a first background image of the front background model and a second background image of the back background model; the first background image is updated according to a scene image; the second background image is updated according to the updated first background image; for a detected static target position, selective local updating is performed; the first and second background images are subjected to difference value operation; the influence of a shadow of the static target position in natural light on the detected static target position is eliminated by using a shadow inhibition technology; and the images are processed by a morphological processing algorithm, a contour extraction algorithm and the like to form an abandoned object region. The method has relatively high environmental adaptability, timeliness and robustness.

Description

technical field [0001] The invention relates to an image processing technology, in particular to a method for detecting remnants. Background technique [0002] The role and advantages of intelligent video surveillance technology in security precautions and early warnings are becoming more and more obvious, and can replace errors and waste of resources caused by human security monitoring. At present, terrorists carry out terrorist activities by leaving behind dangerous objects, causing explosions or releasing toxic substances, threatening social security. Leftovers usually refer to objects that are carried by a moving subject from moving to stationary, then separated from the moving subject, and have been stationary for a certain period of time and have no subject to belong to. To ensure social security, the detection of suspicious leftover objects has become an indispensable content of security systems in public places such as airports, stadiums, waiting halls and exhibitio...

AI Technical Summary

Problems solved by technology

[0003] However, the current remnant object detection algorithm has poor environmental adaptability, and needs to set different parameters according to different situations. Moreover, according to the passage of time, the remnant objects will often be integrated into the background image, making identification difficult.

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