基于模糊聚類的運動對象分割算法研究
Algorithm of Moving Object Segmentation Based on Fuzzy Clustering
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摘要: 為了從視頻序列中分割出完整的、一致的運動視頻對象，該文使用基于模糊聚類的分割算法獲得組成對象邊界的像素，從而提取對象。該算法首先使用了當前幀以及之前一些幀的圖像信息計算其在小波域中不同子帶的運動特征，并根據(jù)這些運動特征構造了低分辨率圖像的運動特征矢量集；然后，使用模糊C-均值聚類算法分離出圖像中發(fā)生顯著變化的像素，以此代替幀間差圖像，并利用傳統(tǒng)的變化檢測方法獲得對象變化檢測模型，從而提取對象；同時，使用相繼兩幀之間的平均絕對差值大小確定計算當前幀運動特征所需幀的數(shù)量，保證提取視頻對象的精確性。實驗結果證明該方法對于分割各種圖像序列中的視頻對象是有效的。
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關鍵詞:
- 視頻對象; 對象分割; 模糊C-均值聚類
Abstract: In order to obtain Integrated and consistent segmentation of motion video objects, the segmentation algorithm based on fuzzy clustering is used to obtain pixels that constitute boundaries of motion object and extract video objects in the sequence sequentially. The motion properties of the current frame in each wavelet sub-band first are calculated using information of current frame and some frames before it in this algorithm. The set of motion eigenvectors is constructed with these properties. Then, significant change pixels are separated by fuzzy C-mean clustering algorithm based on these motion eigenvectors of low-resolution image. The change detection mash of motion object is obtained with significant change image, instead of frame difference, by conventional method of change detection and video objects are extracted. At the same time, the mean absolute different between consecutive two frames is used to determine number of frames that are used for properties calculation. It ensures accuracy of video objects obtained,. The experimental results demonstrate the algorithm effective. -
Sikora T. The MPEG-4 video standard verification model[J].IEEE Trans.Circuit Syst. Video Technol.1997, 7(1):19-[2]Nack F, Lindsay A T. Everything you wanted to know about MPEG-7: Part 2[J].IEEE Multimedia.1999, 6(3):64-[3]劉龍等. 局部運動場景中運動對象的壓縮域分割算法[J].電子與信息學報.2005, 27(8):1249-瀏覽[4]楊莉等. 視頻運動對象的自動分割. 計算機輔助設計與圖形學報, 2004, 16(3): 301－306.[5]吳思, 林守勛, 張勇東. 基于動態(tài)背景構造的視頻運動對象自動分割. 計算機學報, 2005, 28(8): 1386－1392.[6]Kim C, Hwang J N. Fast and automatic video object segmentation and tracking for content-based application[J].IEEE Trans.on Circuits and Syst. Video Technol.2002, 12(2):122-[7]Kim C, Hwang J N. Object-based video abstraction for video surveillance system[J].IEEE Trans. on Circuits and Syst. Video Technol.2002, 12(12):1128-[8]Huang J C, Hsieh W S. Wavelet-based moving-object segmentation[J].IEEE Electronics Letters.2003, 39(19):1380-[9]Huang J C, Su T S, Hsieh W S. Double-change-detection method for wavelet-based moving-object segmentation[J].IEEE Electronics Letters.2004, 40(13):798-[10]Dufaux F, Konrad J. Efficient, robust and fast global motion estimation for video coding[J].IEEE Trans. Image Processing.2000, 9(3):497-[11]Liew A W C, Shu Hung Leung, Wing Hong Lau. Segmentation for color lip images by spatial fuzzy clustering[J].IEEE Trans. Fuzzy Systems.2003, 11(4):542-[12]Eschrich S, Ke Jingwei, Hall L O, et al.. Fast accurate fuzzy clustering through data reduction[J].IEEE Trans. Fuzzy Systems.2003, 11(2):262- -
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