政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/54653

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/54653

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政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/54653

請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/54653

題名:	影像內容檢索中以社群網絡演算法為基礎之多張影像搜尋 Query by Multiple Images for Content-Based Image Retrieval Based on Social Network Algorithms
作者:	張瑋鈴 Chang, Wei Ling
貢獻者:	沈錳坤 Shan, Man Kwan 張瑋鈴 Chang, Wei Ling
關鍵詞:	影像內容檢索多張影像查詢社群網絡 Content-Based Image Retrieval Multiple Images Search Social Network
日期:	2011
上傳時間:	2012-10-30 11:28:22 (UTC+8)
摘要:	近年來，隨著數位科技快速的發展，影像資料量迅速的增加，因此影像檢索成為重要的多媒體技術之一。在傳統的影像內容檢索技術中，使用影像低階特徵值，例如顏色(Color)、紋理(Texture)、形狀(Shape)等來描述影像的內容並進行圖片相似度的比對。然而，傳統的影像內容檢索僅提供單張影像查詢，很少研究多張影像的查詢。因此，本研究提出一個可針對多張影像查詢的方法以提供多張影像查詢的影像內容檢索。本研究將影像內容檢索結合社群網絡演算法，使用MPEG-7中相關特徵描述子和SIFT做為主要特徵向量，擷取影像的低階影像特徵，透過特徵相似度計算建立影像之間的網絡，並利用社群網絡演算法找出與多張查詢影像相似的影像。實驗結果顯示所提出的方法可精確的擷取到相似的影像。 In recent years, with the faster and faster development of computer technology, the number of digital images is grown rapidly so that the Content-Based Image Retrieval has become one of important multimedia technologies. Much research has been done on Content-Based Image Retrieval. However, little research has been done on query by multiple images. This thesis investigates the mechanism for query by multiple images. First, MPEG-7 image features and SIFT are extracted from images. Then, we calculate the similarity of images to construct the proximity graph which represents the similarity structure between images. Last, processing of query by multiple images is achieved based on the social network algorithms. Experimental results indicate the proposed method provides high accuracy and precision.
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Ma, “Fuzzy Color Histogram and Its Use in Color Image Retrieval,” IEEE Transactions on Image Processing, Vol. 11, No. 8, pp. 944-952, 2002. [7] R. Hess, “An Open-Source SIFT Library,” In Proc. of the ACM International Conference on Multimedia, pp.25–29, 2010. [8] T. S. Huang, S. Mehrotra, and K. Ramachandran, “Multimedia Analysis and Retrieval System (MARS) Project,” In Proc. of 33rd Annual Clinic on Library Application of Data Processing-Digital Image Access and Retrieval, 1996. [9] E. Kasutani, A. Yamada, “The MPEG-7 Color Layout Descriptor: a Compact Image Feature Description for High-speed Image/Video Segment Retrieval,” In Proc. of International Conference on Image Processing, pp. 674-677, 2001. [10] H. K. Kim, J. D. Kim, D. G. Sim, and D. I. Oh, “A Modified Zernike Moment Shape Descriptor Invariant to Translation, Rotation and Scale for Similarity-Based Image Retrieval,” In Proc. of the IEEE International Conference on Multimedia and Expo, pp. 307-310, 2000. [11] J. J. Koenderink, “The Structure of Images,” Biological Cybernetics, Vol. 50, No. 5, pp. 363-396, 1984. [12] H. J. Lin, Y. T. Kao, S. H. Yen, and C. J. Wang, “A Study of Shape-Based Image Retrieval,” In Proc. of 24th International Conference on Distributed Computing Systems Workshops, pp. 118-123, 2004. [13] T. Lindeberg, “Scale-space Theory: A Basic Tool for Analyzing Structures at Different Scales,” Journal of Applied Statistics, Vol. 21, No. 2, pp. 224-270, 1994. [14] D. Lowe, “Distinctive Image Features from Scale-invariant Keypoints,” International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110, 2004. [15] B. S Manjunath, G. M. Haley, and D. F. Dunn, “Efficient Gabor Filter Design for Texture Segmentation,” Pattern Recognition, Vol. 29, No. 12, pp. 2005-2016, 1996. [16] B. S. Manjunath, J.-R. Ohm, V. V. Vasudevan, and A. Yamada, “MPEG-7 Color and Texture Descriptors,” IEEE Transactions on Circuit and System for Video Technoloy, Vol. 11, No. 6, pp. 703-715, 2001. [17] B. S. Manjunath, P. Salembier, and T. Sikora,” Introduction to MPEG-7: Multimedia Content Description Standard,” New York: Wiley, 2001. [18] J. M. Martinez, “Standards-MPEG-7 Overview of MPEG-7 Description tools, Part 2,” IEEE Multimedia, Vol. 9, No. 3, pp. 83-93, 2002. [19] W. Niblack, R. Barber, W. Equitz, et al , “The QBIC Project: Querying Images by Content using Color, Texture, and Shape,” In Proc. of SPIE Electronic Imaging: Science and Technology, 1993. [20] J. S Payne, T. J. Stonbam, “Can Texture and Image Content Retrieval Methods Match Human Perception,” In Proc. of Intelligent Multimedia, Video and Speech Processing, pp.154-157, 2001. [21] A. Pentland, R.W. Picard, and S. Sclaroff, “Photobook : Tools for Content-Based Manipulation of image databases, ” International Journal of Computer Vision , Vol.18, pp. 233-254, 1996. [22] K. Porkaew , S. Mehrotra, and M. Ortega, “Query Reformulation for Content Based Multimedia Similarity Retrieval in Mars,” In Proc. of IEEE Conference on Multimedia Computing and Systems,pp.747-751, 1999. [23] Y. Rui, T. Huang, and S. Mehrotra, “Content-Based Image Retrieval with Relevance Feedback in MARS,” In Proc. of IEEE International Conference on Image Processing , pp. 815-818, 1997. [24] T. Sikora, “The MPEG-7 Visual Standard for Content Description-An Overview, “ IEEE Transactions on Circuits Systems for Video Technology, Vol. 11, No. 6, 2001. [25] J. R. Smith and S. F. Chang, “Visualseek: A Fully Automated Content-Based Image Query System,” In Proc. of the ACM International Multimedia Conference, pp.87-98, 1996. [26] J. R. Smith, Integrated Spatial and Feature Image Systems: Retrieval, Compression and Analysis, PhD Thesis, Graduate School of Arts and Sciences, Columbia University, 1997. [27] M. Sozio and A. Gionis, “The Community-Search Problem and How To Plan A Successful Cocktail Party,” In Proc. of 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’10, pp.939-948, 2010. [28] P. Y. Yin , S. H. Li, “Content-Based Image Retrieval Using Association rule Mining with Soft Relevance Feedback” Journal of Visual Communication and Image Representation, Vol.17, No. 5, pp.1108-1125, 2006. [29] Y. Zhang, M.A. Nascimento, and O.R. Zaiane, “Building Image Mosaics: An Application of Content-Based Image Retrieval,” In Proc. of IEEE International Conference on Multimedia and Exposition, 2003. [30] “MPEG-7 Visual Experimentation Model (XM) Version 10,” ISO/IEC/JTC1/SC29/WG11, Doc. N4063, 2001. [31] “Overview of the MPEG-7 Standard Version 5.0,” Final Committee Draft, ISO/IECJTC1/SC29/WG11, Doc. N4031, 2001.
描述:	碩士國立政治大學資訊科學學系 98971005 100
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0989710051
資料類型:	thesis
顯示於類別:	[資訊科學系] 學位論文

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