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研究生:黃偉城
研究生(外文):Wei-Cheng Huang
論文名稱:以建構背景擷取運動物件之方法
論文名稱(外文):Moving Object Segmented by Background Construct
指導教授:陳玲慧陳玲慧引用關係
學位類別:碩士
校院名稱:國立交通大學
系所名稱:資訊科學系所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:93
語文別:中文
論文頁數:50
中文關鍵詞:運動物件切割影片壓縮建構背景分水嶺
外文關鍵詞:motion objectsegmentationvideo compressionbackground constructionwatershed
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以物件為基礎的影片壓縮方法當中,壓縮的效率跟運動物件的擷取是成正比的,若是運動物件的擷取越準確,則其壓縮的效率越好。在此篇論文當中,我們分別對時間域跟空間域做分割,再將兩種結果結合。在空間上我們利用分水嶺演算法,將空間上的特徵資訊找出來。在時間方面,我們將連續畫面相減,然後以自動產生的門檻值判別影像是否有改變,利用此項資訊,建構一個可靠的背景,當一個像素連續多個畫面被判定為沒有改變的像素,則此像素是背景像素,我們便將它建構成背景。最後,將目前的畫面跟背景影像比較而定義出移動物件遮罩。此遮罩再與分水嶺演算法的結果整合即可準確的將物件切割出來。
In the method of the object-base compression video, the compression performance and the motion object segmented are in the direct proportion. If the motion object segmented is more accurate, the compression performance is better. In this paper, we segment the object on the temporal domain and the spatial domain , and then we combine the results of them. In spatial domain, we use the watershed algorithm to find out the characteristics of the spatial domain. In the temporal domain, we subtract the constant frames, and then we determine the frames by the threshold of auto generated if change or not. We make use of this information to construct a reliable background. If the constant frames of pixel are categorized to an unchangeable pixel, the pixel is background pixel. We will construct it to the background. Finally, we compare the current frame with the background to define the motion object mask. The combination of the object mask and the result of Watershed Algorithms is able to segment the objects exactly.
目錄

摘要 ………………………………………………………………i
Abstract ……………………………………………………….ii
誌謝 ……………………………………………………………iii
目錄 …………………………………………………………….iv
LIST OF TABLE ……………………………………………....vi
LIST OF FIGURES …………………………………………….vii
第一章 緒論……………………………………………………1
1.1 研究動機…………………………………………….......1
1.2 相關研究討論…………………………………….........2
1.3 論文架構.……………………………………………......4
第二章 空間域的切割……………………………………………6
2.1 Morphological Gradient…………………………….....6
2.2 分水嶺切割(Watershed segmentation)……………....11
2.2.1 用氾濫(immersion)模擬的分水嶺演算………….....11
2.2.2 分水嶺演算法之實現……………………………......12
第三章 時間域的切割………………………………………….15
3.1概要………………………………………………….......15
3.2演算法的整個流程………………………………….......16
3.2.1畫面差(Frame Difference)……………………….....17
3.2.2背景的建構(Background Construction)…………....19
3.2.3背景-目前畫面差(Background-Current Frame
Difference)…………………………………….............21
3.2.4 偵測物件(object detection)………………………..23
3.2.5後續的處理(post process)……………………….....27
3.3 門檻值的自動產生………………………………........29
第四章 空間-時間域切割及實驗結果…………………………37
4.1結合時間域跟空間域的切割…………………….........37
4.1.1移動區域的偵測………………………………….......37
4.1.2移動邊界的偵測………………………………….......40
4.2實驗結果………………………………………….........41
第五章 結論…………………………………………………….48
REFERENCES…………………………………………………....49
REFERENCES
[1] “MPRG-4 Video Verification Model version 18.0” ISO/IEC JTC1/SC29/WG11 N3908,January 2001.
[2] “Information Technology – Coding of audio visual objects Part 2:Visual” ISO/IEC 14496-2:2003.
[3]D. Comaniclu and P. Meer, “Mean Shift Analysis and Applications”, Proc. IEEE International Conference on Computer Vision,VOL.2,pp.1179-1203,1999.
[4] D. Comaniclu and P. Meer ,“Mean Shift :A Robust Approach Toward Feature Space Analysis”,Proc. IEEE Transactions on Pattern Analysis and Machine Intelligence,VOL.24,NO.5,pp.603-619,May,2002.
[5]L. Vincent and P. Soille “Watersheds in Digital Space: An Efficient Algorithm Based on Immersion Simulations”, Proc. IEEE Transactions on Pattern Analysis and Machine Intelligence,VOL.13 , NO.6 ,pp.583-598, June,1991.
[6]A.Caplier , L.Bonnaud and J.-M.Chassery, “Robust fast extraction of video objects combining frame differences and adaptive reference image”,Proc. IEEE International Conference on Image Processing ,VOL.2,pp.785-788,2001.
[7] J.-B. Kim and H.-J. Kim, “Efficient region-based segmentation for a video monitoring system”,Proc. Pattern Recognition Letters 24,pp.113-128,2003.
[8]M. Kim , J.-G. Choi ,D. Kim ,H. Lee ,M.-H Lee ,C. Ahn ,Y.-S. Ho “,A VOP generation tool: automatic segmentation of moving objects in image sequences based on spatio-temporal information” ,Proc. IEEE Trans. Circuit and System for Video Technology. VOL.9,No8 ,pp. 1216-1226,Dec 1999.
[9]C. Stiller and J. Konrad , “Estimation motion in image sequences”, IEEE Signal Processing Magazine . VOL.16,Iss. 4,pp 70-91,July 1999.
[10]S.-Y. Chien ,S.-Y. Ma and L.-G. Chen, “Efficient Moving Object Segmentation Algorithm Using Background Registration Technique”, IEEE Trans. Circuit and System for Video Technology. VOL.12 ,No.7,pp.577-586,July,2002.
[11]Wei-Jung Chien and Sheng-Jhy Wang , “The Study of Spatio-Temporal segmentation for image sequences”, Master Thesis, National Chiao Tung University, Hsinchu ,Taiwan,ROC,2001.
[12]R.C. Gonzalez and R.E. Woods, “Digital image Processing”, Addison Wesley Publishing Company,USA,1992.
[13]Linda G. Shapiro and George C. Stockman, “Computer Vision”, Prentice Hall,2001.
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