A novel moving objects segmentation method is proposed in this paper. A modified three dimensional recursive search （3DRS） algorithm is used in order to obtain motion information accurately. A motion feature descrip...A novel moving objects segmentation method is proposed in this paper. A modified three dimensional recursive search （3DRS） algorithm is used in order to obtain motion information accurately. A motion feature descriptor （MFD） is designed to describe motion feature of each block in a picture based on motion intensity, motion in occlusion areas, and motion correlation among neighbouring blocks. Then, a fuzzy C-means clustering algorithm （FCM） is implemented based on those MFDs so as to segment moving objects. Moreover, a new parameter named as gathering degree is used to distinguish foreground moving objects and background motion. Experimental results demonstrate the effectiveness of the proposed method.展开更多
This paper presents a fuzzy C- means clustering image segmentation algorithm based on particle swarm optimization, the method utilizes the strong search ability of particle swarm clustering search center. Because the ...This paper presents a fuzzy C- means clustering image segmentation algorithm based on particle swarm optimization, the method utilizes the strong search ability of particle swarm clustering search center. Because the search clustering center has small amount of calculation according to density, so it can greatly improve the calculation speed of fuzzy C- means algorithm. The experimental results show that, this method can make the fuzzy clustering to obviously improve the speed, so it can achieve fast image segmentation.展开更多
基金Supported by the National Natural Science Foundation of China （No. 60772134, 60902081, 60902052） the 111 Project （No.B08038） the Fundamental Research Funds for the Central Universities（No.72105457）.
文摘A novel moving objects segmentation method is proposed in this paper. A modified three dimensional recursive search （3DRS） algorithm is used in order to obtain motion information accurately. A motion feature descriptor （MFD） is designed to describe motion feature of each block in a picture based on motion intensity, motion in occlusion areas, and motion correlation among neighbouring blocks. Then, a fuzzy C-means clustering algorithm （FCM） is implemented based on those MFDs so as to segment moving objects. Moreover, a new parameter named as gathering degree is used to distinguish foreground moving objects and background motion. Experimental results demonstrate the effectiveness of the proposed method.
文摘This paper presents a fuzzy C- means clustering image segmentation algorithm based on particle swarm optimization, the method utilizes the strong search ability of particle swarm clustering search center. Because the search clustering center has small amount of calculation according to density, so it can greatly improve the calculation speed of fuzzy C- means algorithm. The experimental results show that, this method can make the fuzzy clustering to obviously improve the speed, so it can achieve fast image segmentation.
