# 臺灣博碩士論文加值系統

(3.236.84.188) 您好！臺灣時間：2021/07/30 01:24

:::

### 詳目顯示

:

• 被引用:0
• 點閱:171
• 評分:
• 下載:0
• 書目收藏:0
 本篇論文使用一種記錄輪廓特質的方法，來當圖形的形狀描述子。這個方法是將輪廓用 n 個不連續的點表示，對於每一個參考點，記錄剩下n – 1個點和參考點的相對位置。可以由研究發現，當輪廓被旋轉時，這樣的記錄結果也會被旋轉，因此，如果這些結果彼此有旋轉關係的話，就把他群聚在一起，並且用一個來符號表示。所以，本來輪廓是由 n 個點來表示的，現在變成用n個符號來表示。對於每個輪廓，統計這些符號出現的次數後再與資料庫中的圖片做比對，就可以快速地找到輪廓相似，或是輪廓經由旋轉過後相似的圖。 本篇論文把這種輪廓比對的技巧，套用在3D影像擷取系統中，這個系統是將3D圖片轉換成2D圖片，以各種不同角度的2D圖片來呈現3D圖片的場景，是一個符合人類思考模式的系統。如此一來，對於3D影像擷取的結果將會有很高的準確性。
 In this work we use shape context as our shape descriptor. The representation for a shape is a discrete set of n points. For each of these points, the shape context is a histogram of the relative positions of the remaining points. When a shape is rotated, the shape context is rotated too. We group the rotated shape contexts together and then label each group by an integer. Therefore, a shape is represented by a set of label. Using the histogram of label frequencies can quickly and efficiently search for similar or rotational shapes. We use this shape retrieval method to integrate with an 3D existent retrieval system. This system transforms the 3D pictures to the 2D pictures, using each kind of different angle's 2D pictures to present scenes of 3D pictures. The system will learn the user’s semantic subjectivity. Hence, well accuracy is demonstrated in the results of image retrieval.
 摘要ABSTRACTCONTENTSLIST OF FIGURESChapter 1 Introduction 11.1 Image Retrieval System 11.2 Feature Descriptor 41.3 Organization of the Thesis 5Chapter 2 Region-Based Image Retrieval Using Shape Context 62.1 Region-Based Image Retrieval System Overview 62.1.1 Image Segmentation 72.1.2 Feature extraction 72.1.3 Feature Matching 82.2 Shape Context 82.3 Rotation Invariance 112.3.1 Properties of Rotational Shape Context 122.3.2 Similarity Measure 132.4 Modified K-Means Cluster 14Chapter 3 Reflection Invariance 223.2 Viewpoints 233.3 Rotation Invariance 283.4 New 3D Image Retrieval System 30Chapter 4 Experimental Results 31Chapter 5 Conclusions 39REFERENCES 40
 [1]A. Ghosh and N. Petkov, “Robuatness of Shape Descriptors to Incomplete Contour Representations,” IEEE trans. Pattern Analysis and Machine Intelligence, vol. 27, pp. 1793－1804, 2005.[2]A. Thayananthan, B. Stenger, “Shape Context and Chamfer Matching in Cluttered Scenes,” Proc. IEEE Comp. Soc. Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 127－133, 2003.[3]B. Leibe and B. Schiele, “Analyzing Appearance and Contour Based Methods for Object Categorization,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 409 – 415, 2003.[4]C. Faloutsos, R. Barber, M. Flickner, J. Hafner, W. Niblack, D. Petkovic and W. Equitz, “Efficient and Effective Querying by Image Content,” Journal of Intelligent Systems, pp. 231－262, 1994.[5]C. T. Hsu, “Research of Multimedia Processing Laboratory,” (http://mp.cs.nthu.edu.tw/research.htm)[6]D. Liu and T. Chen, “Soft Shape Context for Iterative Closest Point Registration,” International Conf. Image Processing, vol. 2, pp. 24－27, 2004.[7]F. Jing, M. Li, H. J. Zhang, and B. Zhang, “Relevance Feedback in Region-Based Image Retrieval,” IEEE Trans. Circuits and Systems for Video Technology, vol. 14, pp. 672 – 681, 2004.[8]F. Jing, M. Li, H. J. Zhang, and B. Zhang, “An Efficient and Effective Region-Based Image Retrieval Framework,” IEEE Trans. Image Processing, vol. 13, pp. 699 – 709, 2004.[9]F. Mokhtarian and A. K. Mackworth, “A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, pp. 789－805, 1992.[10]F. Jing, M. Li, H. J. Zhang, and B. Zhang, “Unsupervised Image Segmentation Using Local Homogeneity Analysis,” Proc. IEEE Int. Symp. Circuits and Systems, vol. 2, pp. 456 – 459, 2003.[11]F. Mokhtarian and R. Suomela, “Robust Image Corner Detection Through Curvature Scale Space,” IEEE trans. Pattern Analysis and Machine Intelligence, vol. 20, pp. 1376－1381, 1998.[12]G. Mori, S. Belongie and J. Malik, “Shape Contexts Enable Efficient Retrieval of Similar Shapes,” Proc. IEEE Comp. Soc. Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 723－730, 2001.[13]G. Mori, S. Belongie and J. Malik, “Efficient Shape Matching Using Shape Contexts,” IEEE trans. Pattern Analysis and Machine Intelligence, vol. 27, pp. 1832－1837, 2005.[14]G. Carneiro and A. D. Jepson, “Pruning Local Feature Correspondences Using Shape Context,” Proc. Int. Conf. Pattern Recognition, vol. 3, pp. 16－19, 2004.[15]H. Zhang and J. Malik, “Learning A Discriminative Classifier Using Shape Context Distances,” Proc. IEEE Comp. Soc. Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 242－247, 2003.[16]J. Huang, S. R. Kumar, M. Mitra, W.-J. Zhu, and R. Zabih, “Image Indexing Using Color Correlograms,”Proc. IEEE Comp. Soc. Conf. Computer Vision and Pattern Recognition, pp. 762－768, 1997.[17]J. Z. Wang, J. Li, and G. Wiederhold, ”SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, pp. 947 – 963, 2001.[18]J. Li, J. Z. Wang, and G. Wiederhold, “IRM: Integrated Region Matching for Image Retrieval,” Proc. of the 8th ACM Int. Conf. on Multimedia, pp. 147 – 156, 2000.[19]K. Vu, K. A. Hua, and W. Tavanapong, “Image Retrieval Based on Regions of Interest,” IEEE Trans. Knowledge and Data Engineering, vol. 15, pp. 1045 – 1049, 2003.[20]M. Stricker and M. Orengo, “Similarity of Color Images,” Proc. SPIE Storage and Retrieval for Image and Video Databases III, vol. 2420, pp. 381 – 392, 1995..[21]M. Yusuf and T. Haider, “Recognition of Handwritten Urdu Digits Using Shape Context,” Proc. Int. Multitopic Conference, pp. 569－572, 2004.[22]R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. Reading, MA: Addison-Wesley, 1999[23]S. Belongie and J. Malik, “Matching with Shape Contexts,” IEEE proc. Content-Based Access of Image and Video Libraries, pp. 20－26, 2000.[24]S. Belongie, J. Malik and J. Puzicha, “Shape Matching and Object Recognition Using Shape Contexts,” IEEE trans. Pattern Analysis and Machine Intelligence, vol. 24, pp. 509－522, 2002.[25]“The Math Works,” (http://www.mathworks.com/)[26]W. C. Yen, “Image Retrieval by Using Shape Context,” Department of E.E. NCKU, Tainan, Taiwan, R.O.C., 2006.[27]X. J. Qiu, Z. Q. Wang, S. H. Xia and J. T. Li, “Estimating Articulated Himan Pose from Video Using Shape Context,” Proc. IEEE Int. Symp. Signal Processing and Information Technology, pp. 583－588, 2005.[28]Y. Deng, B. S. Manjunath, C. Kenney, M.S. Moore and H. Shin, “An Efficient Color Representation for Image Retrieval,” IEEE Trans. Image Processing, vol. 10, pp. 140－147, 2001.[29]Ding-Yun Chen, Xiao-Pei Tian, Yu-Te Shen and Ming Ouhyoung, “Shape Distributions,” Computer Graphics Forum (EUROGRAPHICS'03), Vol. 22, No. 3, pp. 223－232, Sept. 2003.[30]Johan W.H. Tangelder, Remco C. Veltkamp, “A survey of content based 3D shape retrieval methods,” Shape Modeling Applications, Proceedings 2004 pp. 145－156, 2004.[31]Yi Liu, Jiantao Pu, Guyu Xin, Hongbin Zha, Weibin Liu, Yusuke Uehara, “A Robust Method for Shape-based 3D Model Retrieval,” Computer Graphics and Applications, 2004. PG 2004. Proceedings. 12th Pacific Conference on 6-8 Oct. 2004, pp. 3－9.[32]Dong Xu, Hua Li, Zongkai Lin, “Content-based 3-D Shape Retrieval for Pervasive Computing,” Pervasive Computing and Applications, 2006 1st International Symposium on 3-5 Aug. 2006, pp. 206－211.[33]3DCAFE, http://www.3dcafe.com.[34]Chia-Hui Lin, “Region-Based Image Retrieval Using Shape Context,” Department of E.E. NCKU, Tainan, Taiwan, R.O.C., 2007.
 國圖紙本論文
 連結至畢業學校之論文網頁點我開啟連結註: 此連結為研究生畢業學校所提供，不一定有電子全文可供下載，若連結有誤，請點選上方之〝勘誤回報〞功能，我們會盡快修正，謝謝！
 推文當script無法執行時可按︰推文 網路書籤當script無法執行時可按︰網路書籤 推薦當script無法執行時可按︰推薦 評分當script無法執行時可按︰評分 引用網址當script無法執行時可按︰引用網址 轉寄當script無法執行時可按︰轉寄

 無相關論文

 無相關期刊

 1 以輪廓特質作影像擷取之研究 2 以輪廓特質作區域性影像擷取之研究 3 閱讀能力與網路使用程度對圖片搜尋的影響 4 全球資訊網圖片搜尋引擎 5 利用最適橢圓正規化之輪廓特質比對 6 光通訊分碼多重擷取技術及光纖微波擷取網路之非線性效應的探討 7 應用於奈米磁粒之半橋串聯諧振式雙頻耦合熱療加熱系統 8 新型可規劃對數型數位層級感測器 9 可變動調頻電刺激系統及應用於生理適應性之評估 10 以心率變異評估『可程式控制-電腦輔助教學系統』對學生反應之研究 11 空載光達航帶重疊區點雲資料之系統性高程偏差量偵測與分析 12 利用多時期航拍影像探討地層下陷歷史變化 13 使用圖片搜尋的直覺式字典 14 基於內容為主之圖片與影像縮放最佳化研究 15 將反轉檔案應用於以視覺文字為基礎的圖片搜尋系統

 簡易查詢 | 進階查詢 | 熱門排行 | 我的研究室