Moving object detection method resisting illumination variation

Abstract

The invention relates to a moving object detection method resisting illumination variation. An existing moving object detection method is sensitive to the illumination variation frequently, and therefore when illumination variation occurs in a detection environment, accurate detection for a moving object is difficult. The moving object detection method resisting the illumination variation integrates an asymmetrical inter-frame difference method and a self-adaptation mixed gauss background difference method in inter-frame difference. The moving object detection method resisting the illumination variation includes a first step of preprocessing an input moving image, a second step of respectively conducting asymmetrical inter-frame difference moving object detection and self-adaptation mixed gauss background difference moving object detection, and a third step of comparing moving object results independently obtained through the two detection methods, calculating the moving object results, extracting a comprehensive moving object, filling cavities inside the moving object and filtering out some small interference through mathematics morphological processing. Through the moving object detection method resisting the illumination variation, the moving object can be accurately detected under the normal condition, and meanwhile the accuracy rate can reach over 90% under the condition that the illumination variation of the detecting environment occurs. Therefore, the moving object detection method resisting the illumination variation can meet needs of a monitoring system.

Description

technical field [0001] The invention belongs to the field of image processing in a video monitoring system, and relates to a moving target detection method resistant to illumination changes in a detection environment. Background technique [0002] With the rapid development of digital network technology, video images have become an important carrier of information transmission. The large and rich motion information contained in video image sequences has aroused great interest. Although human eyes can directly distinguish moving objects and extract moving information from video image sequences, only relying on human natural intelligence to acquire and process moving information can no longer meet the needs of social development. Using computer vision to replace human vision, extracting, analyzing and understanding motion information from image sequences has become a popular direction in the field of modern scientific research. The detection of moving objects in video image s...

AI Technical Summary

Problems solved by technology

The actual scene is complex. Changes in weather and lighting conditions, shadows accompanied by moving objects, moving in and out of other objects, mutual occlusion between objects, and real-time requirements for algorithms, etc., all cause difficulties in moving object detection and tracking.

Therefore, it is still a challenging subject to study robust, accurate and high-performance moving target detection and tracking algorithms.

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