Research Of Movement Objects Segmentation Technology In Video Surveillance

Video surveillance technology is the new-emerging application direction in the filed of Computer Vision and is attracting more and more attention.It spans many subjects including computer science,machine vision,image engineering,pattern recognition, artificial intelligence and so on.It widely applies in city road traffic surveillance and security surveillance.The movement objects segmentation is the key technology in video surveillance.The veracity of segmentation directly affects the effectiveness of latter tasks.So it has very important meaning.At present,there have many excellent segmentation algorithms for video objects,but these algorithms are proposed in special application environment.The automatic video segmentation algorithm that can use in any scene is still a classical difficulty need to be solved.The video objects segmentation algorithms are deeply studied based on LK Optical Flow and Mixture Gaussian Model in this thesis.Through a great deal of experiments,the thesis acquired a series of valuable results which can be summarized in the following aspects:1.On the basis of analyzing the performance of existing Optical Flow methods,an improved algorithm is presented.This thesis uses Gaussian pyramid reduce the speed of movement objects,and then segments pictures use Gaussian distribution combine with LK Optical Flow.The algorithm improves the real-time capability and can get more accurate movement objects.2.Considering the extraction effects of initial background frame directly impact the performance of background modeling,an MEAMO algorithm of producing initial background frame is proposed based on existing methods.The algorithm can decrease the initial error and it is helpful to achieve the latter tasks. 3.For the shadows produce serious impacts to movement objects segmentation,an adaptive shadows detection algorithm based on Mixture Gaussian Model is presented. Choosing CIE LUV color space,the paper uses L weight do background modeling,and then uses Gaussian distribution do adaptive shadows detection for the ratio of foreground's L weight and background's L weight.The algorithm achieves adaptive shadows detection.It has strong robustness and high accuracy.In conclusion,this thesis makes farther research for the segmentation algorithms in video surveillance.The experimental results of each researched algorithm are intending and good.