Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19401
標題: 以形狀相似性比對之影像擷取系統
Image Retrieval by Shape Similarity
作者: 陳正宜
CHEN, CHENG-I
關鍵字: Content-Based Image Retrieval
以內容為基礎的影像擷取
Multiresolution
quadtree
多重解析度
四元樹
出版社: 資訊科學系所
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Faloutsos. “Similarity searching in medical image databases,” IEEE Trans. Knowledge and Data Engineering, vol. 9, no. 3, 1997. [8] E.G. M. Petrakis, A. Diplaros, E. Milios, “Matching and retrieval of distorted and occluded shapes using dynamic programming,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no.11, 1501-1516, 2002. [9] E.M. Voorhees and D.K. Harmann. Overview of the Seventh Text REtrieval Conference (TREC-7). In NIST Special Publication 500-242: The Seventh Text REtrieval Conference, 1-23, 1998. (http://trec.nist.gov/pubs/trec7/t7 proceedings.html). [10] F. Mahmoudi, J. Shanbehzadeh, A.-M. E.-Moghadam, S.-Z. Hamid. “Image retrieval based on shape similarity by edge orientation autocorrelogram,” Pattern Recognition, vol. 36, 1725-1736, 2003. [11] F. Mokhtarian, A. K. Mackworth. “A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 8, 1992. [12] F. Morkhtarian, M. Bober, “Curvature Scale Space Representation: Theory, Applications & MPEG-7 standardization,” Kluwer Academic Publishers, Dordrecht, 2003. [13] F. Morkhtarian, S. Abbasi, and J. Kittler, “Efficient and robust retrieval by shape content through curvature scale space,” Image Databases and Multi-Media Search, 35-42, 1996. [14] G. Granlund, “Fourier preprocessing for hand print character recognition,” IEEE Transactions on Computer, vol. 21, 195-201, 1972. [15] Yoo, H.W, Park, H.S, Jang, D.S, “Expert system for color image retrieval,” Expert System with Applications, vol. 28, 347-357,2005. [16] Huang, P.W., Dai, S.K., Lin, P.L and Kuo, R.T. “Similarity retrieval based on grouping bounding and angle sequence matching in shape database systems,” Journal of Systems and Software, vol. 54, no.1, 9-16, 2000. [17] I. Ahmad, W. I. Grosky, “Indexing and retrieval of images by spatial constraints,” Journal of Visual Communication and Image Representation, vol. 14, 291-320, 2003. [18] K.-L Tan, B.C. 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摘要: 在這篇論文中,我們提出新的方法來設計以形狀特徵做為比對標準之影像擷取資訊系統。 在形狀相似的影像擷取中,我們使用新的形狀分解方法擷取出兩個形狀特徵,一個為形狀的輪廓點個數在每個象限中所佔之比重,另一個為形狀輪廓點與兩條第一層象限切割線所交集的個數。藉由我們所提出之方法,內部具有空洞的形狀可以輕易地被處理。在第一階段中,我們使用group bounding的機制來縮小資料庫的搜尋範圍,因而加快整個查詢速度。在第二階段中,我們採用四元樹結構搭配我們所提出的比對方法來進行形狀的比對,並根據我們所定義的相似性測量法計算出形狀影像之間的差異度,最後依據所計算出的差異度以遞增的方式將相似的影像輸出。實驗的結果顯示我們所提出的方法不但有效率而且更能精確地搜尋出相似的形狀影像。
In this thesis, we propose a new method for the design of a content-based image retrieval system based on shape. In our shape similarity retrieval, two shape features are extracted by using a new shape decomposition scheme. One is the proportion of the number of contour points in each quadrant, and the other is the number of contour points intersecting with the two level-1 quadrant-segmentation lines. With our proposed scheme, the shapes that have holes inside them can be handled. When a query shape is submitted to the system, the number of contour points intersecting with the two level-1 quadrant-segmentation lines is used along with a tolerance value to generate the lower bound and upper bound. Then, the shapes between these two bounds are compared to the query shape by using the proportion of the number of contour points in each quadrant. This will restrict the search space to a reasonable small proportion of the whole database. Finally, the shapes are displayed to user with increasing order based on their difference value. The experimental results show that our proposed scheme is efficient and accurate when search similar images.
URI: http://hdl.handle.net/11455/19401
其他識別: U0005-2908200612192000
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-2908200612192000
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