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Image Information Retrieval Based on Shapes and Spatial Relations for Pictures Containing Sized Objects
|關鍵字:||shape;形狀;spatial relation;image database;空間關係;影像資料庫||出版社:||應用數學系所||引用:|| D. Androutsos, K. N. Plataniotis and A.N. Venetsanopoulos, “A Novel Vector-based Approach to Color Image Retrieval Using a Vector Angular-based Distance Measure,” Computer Vision and Image Understanding, vol. 75, no. 1-2, pp. 46-58, 1999.  J. R. Bach, C. Fuller, A. Gupta, A. Hampapur, B. Horowitz, R. Humphrey, R.C. Jain and C. Shu, “Virage Image Search Engine: an Open Framework for Image Management,” Proc. Symposium on Electronic Imaging: Science and Technology-Storage & Retrieval for Image and Video Database IV, IS&T/SPIE, pp. 76-87, 1996.  Andrew P. Berman, and Linda G. Shapiro, “A Flexible Image Database System for Content-based Retrieval,” Computer Vision and Image Understanding, vol. 75, no. 1-2, pp. 175-195, 1999.  S. Berretti, A. Del Bimbo, and E. Vicario, “Spatial Arrangement of Color in Retrieval by Visual Smilarity,” Pattern Recognition, vol. 35, no. 8, pp. 1661-1674, 2002.  B. Bhanu and S. Lee, “Genetic Learning for Adaptive Image Segmentation,” Norwell: Kluwer Academic, 1994.  S. K. Bhatia and C. L. Sabharwal, “A Fast Implementation of a Perfect Hash Function for Picture Objects,” Pattern Recognition, vol. 27, pp. 365-376, 1994.  Roland Billen and Siyka Zlatanova, “3D Spatial Relationships Model: A Useful Concept for 3D Cadastre?,” Computers, Environment and Urban Systems, vol. 27, no. 4, pp. 411-425, 2003.  Ernesto Bribiesca, “A New Chain Code,” Pattern Recognition, vol. 32, pp. 235-251, 1999.  Guang-Ho Cha and Chin-Wan Chung, “An Indexing and Retrieval Mechanism for Complex Similarity Queries in Image Databases,” Journal of Visual Communication and Image Representation, vol. 10, no. 3, pp. 268-290, 1999.  Youssef Chahir and Liming Chen, “Searching Images on the Basis of Color Homogeneous Objects and Their Spatial Relationship,” Journal of Visual Communication and Image Representation, vol. 11, no. 3, pp. 302-326, 2000.  C. C. Chang, “Spatial Match Retrieval of Symbolic Pictures,” Journal of Information Science and Engineering, vol. 7, pp. 405-422, Dec. 1991.  C. C. Chang and S. Y. Lee, “Retrieval of Similar Pictures on Pictorial Databases,” Pattern Recognition, vol. 24, pp. 675-680, 1991.  C. C. Chang and J. H. Jiang, “A Spatial Filter for Similarity Retrieval,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 10, no. 6, pp.711-730, 1996.  C. C. Chang and C. F. Lee, “A Two-level Signature File Based on a Block-Oriented Data Model for Spatial Match Retrieval,” Journal of the Chinese Institute of Engineers, vol. 21, no. 4, pp. 467-478, 1998.  Ning-San Chang and King-Sun Fu, “Query-by-Pictorial-Example,” IEEE Trans. On Software Engineering, vol. 6, no. 6, pp. 519-524, 1980.  S. K. Chang, Q. Y. Shi, and C. W. Yan, “Iconic Indexing by 2D Strings,” IEEE Trans. On Pattern Analysis and Machine Intelligence, vol. 9, no. 3, pp. 413-428, May 1987.  S. K. Chang, E. Jungert, and Y. Li, “Representation and Retrieval of Symbolic Pictures Using Generalized 2D Strings,” Technical Report, University of Pittsburg, 1988.  S. K. Chang, Principles of Pictorial Information Systems Design, Prentice-Hall Inc., Englewood Cliffs, NJ, 1989.  Y. Chen, “Signature Files and Signature Trees,” Information Processing Letters, vol. 82, pp. 213-221, 2002.  Y. Chen and J. Z. Wang, “A Region-based Fuzzy Feature Matching Approach to Content-based Image Retrieval,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no.9, pp. 1252-1267, Sept. 2002.  Yanling Chi and Maylor K. H. Leung, “ALSBIR: A local-structure-based image retrieval,” Pattern Recognition, vol. 40, pp. 244-261, 2007.  M. Chung, R. Wilson, K. Shaw, F. E. Petry and M. A. Cobb, “Querying Multiple Data Sources via an Object-oriented Spatial Query Interface and Framework,” Journal of Visual Language & Computing, vol. 12, no. 1, pp. 37-60, 2001.  R. J. Cichelli, “Minimal Perfect Hash Functions Made Simple,” CACM, vol. 23, pp.17-19, 1980.  L. Cinque, G. Ciocca, S. Levialdi, A. Pellicano and R. Schettini, “Color-based Image Retrieval Using Spatial-chromatic Histograms,” Image and Vision Computing, vol. 19, no. 13, pp. 979-986, 2001.  Sharlee Climer and Sanjiv K. Bhatia, “Image Database Indexing Using JPEG Coefficients,” Pattern Recognition, vol. 35, no. 11, pp. 2479-2488, 2002.  Carlo Colomboa and Alberto Del Bimbo, “Color-induced Image Representation and Retrieval,” Pattern Recognition, vol. 32, no. 10, pp. 1685-1695, 1999.  C. R. Cook, and R. R. Oldehoeft, “A Letter-oriented Minimal Perfect Hashing Function,” ACM SIGPLAN Notices, vol. 17, pp.17-27, 1982.  Vito Di Gesu and Valery Starovoitov, “Distance-based Functions for Image Comparison,” Pattern Recognition Letters, vol. 20, no. 2, pp. 207-214, 1999.  E. Di Sciascio, F. M. Donini and M. Mongiello, “Spatial Layout Representation for Query-by-sketch Content-based Image Retrieval,” Pattern Recognition Letters, vol. 23, no. 13, pp. 1599-1612, 2002.  E. Di Sciascio, M. Mongiello, F. M. Donini, and L. Allegretti, “Retrieval by Spatial Similarity: An Algorithm and a Comparative Evaluation,” Pattern Recognition Letters, vol. 25, No. 14, pp. 1633-1645, 2004.  M. N. Do and M. Vetterli, “Wavelet-based Texture Retrieval Using Generalized Gaussian Density and Kullback-Leibler Distance,” IEEE Trans. Image Processing, vol. 11, no. 2, pp. 146-158, 2002.  A. M. Eftekhari-Moghadam, J. Shanbehzadeh, F. Mahmoudi and H. Soltanian-Zadeh, “Image Retrieval Based on Index Compressed Vector Quantization,” Pattern Recognition, vol. 36, no. 11, pp. 2635-2647, 2003.  Max J. Egenhofer, “A Model for Detailed Binary Topological Relationships,” Geomatica 47(3&4): pp. 261-273, 1993.  Max J. Egenhofer, “Deriving the Composition of Binary Topological Relations,” Journal of Visual Languages and Computing, 5(2): pp. 133-149, 1994.  Max J. Egenhofer, “Query Processing in Spatial-query-by-sketch,” Journal of Visual Languages and Computing, vol.8, pp. 403-424, 1997.  Eyas El-Qawasmeh, “A Quadtree-based Representation Technique for Indexing and Retrieval of Image Databases,” Journal of Visual Communication & Image Representation, vol. 14, pp. 340-357, 2003.  Martin Erwig and Markus Schneider, “Visual Language for the Evolution of Spatial Relationships and Its Translation into a Spatio-temporal Calculus,” Journal of Visual Languages & Computing, vol. 14, no. 2, pp. 181-211, 2003.  M. Flickner, H. Aawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Streele, and P. Yanker, “Query by Image and Video Content: The QBIC System,” Computer, vol. 28, no. 9, pp. 23-32, Sept. 1995.  H. Freeman, “On the Encoding of Arbitrary Geometric Configurations,” IRE Trans. Electron. Comput. EC-10, pp. 260-268, 1961.  Roop K. Goyal, “Similarity Assessment for Cardinal Directions between Extended Spatial Objects,” PhD thesis, Dept. of Spatial Information Science and Engineering, Univ. of Maine, May 2000.  R. Goyal and M. J. Egenhofer, “Similarity of Cardinal Directions,” Lecture Notes in Computer Science, vol. 2121, Springer-Verlag, pp. 36-55, July 2001.  J. Guo and A. Zhang, “Image Decomposition and Representation in Large Image Database Systems,” Journal of Visual Communication and Image Representation, vol. 8, no. 2, pp. 167-181, 1997.  R. Haar, “Computational Models of Spatial Relations,” Technical Report: TR-478, MSC-72-03610, Computer Science, University of Maryland, College Park, MD.  Christian Hennig and Longin Jan Latecki, “The Choice of Vantage Objects for Image Retrieval,” Pattern Recognition, vol.36, pp. 2187-2196, 2003.  K. Hirata and T. Kato, “Query by Visual Example,” Proc. Third Int. Conf. Extending Database Technology: Advances in Database Technology, pp. 56-71, 1992.  P. W. Huang and Y. R. Jean, “Using 2D C+-string as Spatial Knowledge Representation for Image Database Systems,” Pattern recognition, vol.27, no.9, pp. 1249-1257, 1994.  P. W. Huang and Y. R. Jean, “Reasoning about Pictures and Similarity Retrieval for Image Information Systems Based on SK-SET Knowledge Representation,” Pattern Recognition, vol. 28, no. 12, pp. 1915-1925, 1995.  P. W. Huang and Y. R. Jean, “Design of Large Intelligent Image Database Systems,” International Journal of Intelligent Systems, vol. 11, no. 6, pp. 347-365, 1996.  P. W. Huang and Y. R. Jean, “Spatial Reasoning and Similarity Retrieval for Image Database Systems Based on RS-string,” Pattern Recognition, vol. 29, no. 12, pp. 2103-2114, 1996.  P. W. Huang, “Indexing Pictures by Key Objects for Large-scale Image Database,” Pattern Recognition, vol. 30, no. 7, pp. 1229-1237, 1997.  P. W. Huang, S. K. Dai and P. L. Lin, “Planar Shape Recognition by Directional Flow-change Method,” Pattern Recognition Letters, vol. 20, pp. 63-170, 1999.  P. W. Huang and P. L. Lin, “Symbolic Picture Retrieval by Relative-metric Spatial Relations,” International Journal of Intelligent Systems, vol. 15, pp. 525-534, 2000.  P. W. Huang, P. L. Lin, and H. Y. Lin, “Optimizing Storage Utilization in R-tree Dynamic Index Structure for Spatial Databases,” The Journal of systems and software, vol. 55, pp. 291-299, 2001.  P. W. Huang, and S. K. Dai, “Image Retrieval by Texture Similarity,” Pattern Recognition, vol. 36, pp. 665-679, 2003.  P. W. Huang and C. H. Lee, “An Efficient Method of Organizing Bit-string Signatures for Searching Symbolic Images,” Pakistan Journal of Information and Technology, vol. 2, no. 2, pp. 159-172, April-June 2003.  P. W. Huang and C. H. Lee, “Image Database Design Based on 9D-SPA Representation for Spatial Relations,” IEEE Trans. On Knowledge and Data Engineering, vol. 16, no. 11, pp. 1486-1496, November 2004.  Jing Huang, S. R. Kumar, M. Mitra, and Wei-Jing Zhu, “Spatial Color Indexing and Applications,” Computer Vision, Sixth International Conference on, pp. 602-607, 1998.  M. H. Hung, C. H. Hsieh, and C.M. Kuo, “Similarity Retrieval of Shape Images Based on Database Classification,” Journal of Visual Communication and Image Representation, vol. 17, no. 5, pp. 970-985, October 2006.  E. Jungert, “Extended Symbolic Projections as a Knowledge Structure for Spatial Reasoning,” Proc. 4th BPRA Conf. On Pattern Recognition, Springer, Cambridge, pp. 343-351, 1988.  E. Jungert and S. K. Chang, “An Algera for Symbolic Image Manipulation and Transformation,” Visual Database systems, T.L. Kunii, ed., Elsevier Science Publishers B.V., North-Holland, 1989.  Mohan S. Kankanhalli, Babu M. Mehtre and Hock Yiung Huang, “Color and Spatial Feature for Content-based Image Retrieval,” Pattern Recognition Letters, vol. 20, no. 1, pp. 109-118, 1999.  Hannu Kauppinen, Tapio Seppanen and Matti Pietikainen, “An Experimental Comparison of Atoregressive and Fourier-based Descriptors in 2D Shape Classification,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, no.2, 1995.  P. M. Kelly et al., “Query by Image Example: The CANDID Approach,” Proc. SPIE Storage and Retrieval of Image and Video Databases, pp. 238-248, 1995.  Alireza Khotanzad and Orlando J. Hernandez, “Color Image Retrieval Using Multi-spectral Random Field Texture Model and Color Content Features,” Pattern Recognition, vol. 36, no. 8, pp. 1679-1694, 2003.  C. R. Kim, C. W. Chung, “XMage: An Image Retrieval Method Based on Partial Similarity,” Information Processing and Management, vol. 42, no. 2, pp. 484-502, March 2006.  Dong Ho Kim, Keun Ho Ryu and Chee Hang Park, “Design and implementation of spatiotemporal database query processing system,” Journal of Systems and Software, vol. 60, no. 1, pp. 37-49, 2002.  Whoi-Yul Kim and Yong-Sung Kim, “A Region-based Shape Descriptor Using Zernike Moments,” Singnal Processing: Image Communication, vol. 16, pp. 95-102, 2000.  Anthony J. T. Lee and Han-Pang Chiu, “2D Z-string: A New Spatial Knowledge Representation for Image Databases,” Pattern Recognition Letters, vol. 24, pp. 3015-3026, 2003.  C. H. Lee and P. W. Huang, “Image Indexing and Similarity Retrieval Based on Key Objects,” The 2004 IEEE International Conference on Multimedia and Expo (ICME2004), Jun. 27-30 2004 in Taipei, Taiwan, R.O.C.  S. Y. Lee, M. K. Shan and W. P. Yang, “Similarity Retrieval of Iconic Image Database,” Pattern Recognition, vol. 22, no. 6, pp. 675-682, 1989.  S. Y. Lee and F. J. Hsu, “2D C-string: A New Spatial Knowledge Representation for Image Database Systems,” Pattern Recognition, vol. 23, no. 10, pp. 1077-1087, Oct. 1990.  Suh-Yin Lee and Man-Kwan Shan, “Access Methods of Image Database,” Int. J. Pattern Recognition Artificial Intell. vol. 4, no. 1, pp. 27-44, 1990.  S. Y. Lee and F. J. Hsu, “Spatial Reasoning and Similarity Retrieval of Images Using 2D C-string Knowledge Representation,” Pattern Recognition, vol. 25, no. 3, pp. 305-318, 1992.  K. C. Liang and C. C. Jay Kuo, “WaveGuide: A Joint Wavelet-based Image Representation and Description System,” IEEE Trans. On Image Processing, vol. 8, no. 11, pp. 1619-1629, 1999.  Jiming Liu, “A Method of Spatial Reasoning Based on Qualitative Trigonometry,” Artificial Intelligence, vol. 98, no. 1-2, pp. 137-168, 1998.  Xuan Liu, Shashi Shekhar and Sanjay Chawla, “Object-based Directional Query Processing in Spatial Databases,” IEEE Trans. on knowledge and engineering, vol.15, no.2, March/April 2003.  Guojun Lu and Atul Sajjanhar, “Region-based Shape Representation and Similarity Measure Suitable for Content-based Image Retrieval,” Multimedia System 7, pp. 165-174, 1999.  W. Y. Ma and B. S. Manjunath, “Netra: A Toolbook for Navigating Large Image Databases,” Proc. ICIP'97, Santa Barbara, CA, pp. 568-571, 1997.  A. K. Majumdar, I. Bhattacharya, and A. K. Saha, “An Object Oriented Fuzzy Data Model for Similarity Detection in Image Databases,” IEEE Trans. On Knowledge and Data Engineering, vol. 14, no. 5, pp. 1186-1189, Sept./Oct. 2002.  Babu M. Mehtre, Mohan S. Kankanhalli and Wing Foon Lee, “Content-based Image Retrieval Using Composite Color Shape Approach,” Information Processing and Management, vol. 35, no. 1, pp. 109-120, 1998.  T. Minka, “An Image Database Browser That Learns from User Interaction,” Technical Report, MIT Media Lab Perceptual Computing Section, 1995.  T. Minka and R. Picard, “Interactive Learning with a Society of Models,” Pattern Recognition, vol. 30, pp. 565-582, 1997.  Farzin Mokhtarian and Sadegh Abbasi, “Shape Similarity Retrieval under Affine Transforms,” Pattern Recognition, vol. 35, pp. 31-41, 2002.  M. Nabil, J. Shepherd and A. H. H. Ngu, “2D Projection Interval Relationships: A Symbolic Representation of Spatial Relationships,” Lecture Notes in Computer Science, no. 951, pp. 292-309, 1995.  Mohammad Nabil, Anne H. H. Ngu and John Shepherd, “Picture Similarity Retrieval Using the 2D Projection Interval Representation,” IEEE Trans. on Knowledge and Data Engineering, vol. 8, no. 4, pp. 533-539, August 1996.  Mario A. Nascimento, E. Tousidou, V. Chitkara and Yannis Manolopoulos, “Image Indexing and Retrieval Using Signature Trees,” Data and Knowledge Engineering, vol. 43, no. 1, pp. 57-77, 2002.  A. Pentland, R. W. Picard and S. Sclaroff, “Photobook: Tool for Content-based Manipulation of Image Databases,” International Journal of Computer Vision, vol. 18, no. 3, pp. 233-254, June 1996.  E. Petrakis, C. Faloutsos, and K. I. Lin, “ImageMap: An Image Indexing Method Based on Spatial Similarity,” IEEE Trans. On Knowledge and Data Engineering, vol. 14, no. 5, pp. 979-987, Sept./Oct. 2002.  Frederick E. Petry, Maria A. Cobb, Lixiong Wen and Huiqing Yang, “Design of System for Managing Fuzzy Relationships for Integration of Spatial Data in Querying,” Fuzzy Sets and Systems, vol. 140, no. 1, pp. 51-73, 2003.  Donna Jean Peuquet and Zhan Ci-Xiang, “An Algorithm to Determine the Directional Relationship between Arbitrarily-shaped Polygons in the Plane,” Pattern Recognition, vol. 20, no.1, pp. 65-74, 1987.  P. Punitha and D. S. Guru, “An Invariant Scheme for Exact Match Retrieval of Symbolic Images: Triangular Spatial Relationship Based Approach,” Pattern Recognition Letters, vol. 26, pp. 893-907, 2005.  G. Qiu, “Indexing Chromatic and Achromatic Patterns for Content-based Colour Image Retrieval,” Pattern Recognition, vol. 35, no. 8, pp. 1675-1686, 2002.  Y. Rui and T. S. Huang, “Image Retrieval: Current Techniques, Promising Directions, and Open Issues,” J. Visual Comm. Image Representation, vol. 10, pp. 39-62, 1999.  C. L. Sabharwal and S. K. Bhatia, “Perfect Hash Table Algorithm for Image Databases Using Negative Associated Values,” Pattern Recognition, vol. 28, pp. 1091-1101, 1995.  Arnold W. M. Smeulders et al., “Content-based Image Retrieval at the End of the Early Years,” IEEE Trans. Pattern Anal. Machine Intell., vol. 22, pp. 1349-1379, 2000.  J. R. Smith and S. F. Chang, “VisualSEEK: A Full Automated Content-based Image Query System,” Proc. Fourth ACM Int'l Multimedia Conf., pp. 87-98, 1996.  Kian-Lee Tan, Beng Chin Ooi and Lay Foo Thiang, “Indexing Shapes in Image Databases Using the Centroid-radii Model,” Data & Knowledge Engineering, vol. 32, pp. 271-289, 2000.  Y. Tao and W. I. Grosky, “Spatial Color Indexing: A Novel Approach for Content-based Image Retrieval,” Multimedia Computing and Systems, IEEE International Conference on, vol. 1, pp. 530-535, 1999.  James Z. Wang, Jia Li and Gio Wiederhold, “SIMPLicity: Semantics-sensitive Integrated Matching for Picture Libraries,” IEEE Trans. Pattern Anal. Machine Intell., vol. 23, no. 9, pp. 947-963, 2001.  Jae Dong Yang, “An Image Retrieval Model Based on Fuzzy Triples,” Fuzzy Sets and Systems, vol. 121, no. 3, pp. 459-470, 2001.  Dengsheng Zhang and Guojun Lu, “Shape-based Image Retrieval Using Generic Fourier Descriptor,” Signal Processing: Image Communication, vol. 17, pp. 825-848, 2002.  Dengsheng Zhang and Guojun Lu, “Review of Shape Representation and Description Techniques,” Pattern Recognition, vol.37, pp. 1-19, 2004.  Dengsheng Zhang and Guojun Lu, “Study and Evaluation of Different Fourier Methods for Image Retrieval,” Image and Vision Computing, vol. 23, pp. 33-49, 2005.  Yu Zhong and Anil K. Jain, “Object Localization Using Color, Texture and Shape,” Pattern Recognition, vol. 33, pp. 671-684, 2000.  X. M. Zhou and C. H. Ang, “Retrieving Similar Pictures from a Pictorial Database by an Improved Hashing Table,” Pattern Recognition Letters, vol. 18, pp. 751-758, 1997.||摘要:||
在本篇論文中，我們提出兩個影像表示法來幫助建立CBIR (Content-Based Image Retrieval)系統。第一個是以物件形狀為主的影像表示法，稱為NOAR (Normalized Object Area Representation)，第二個是以空間關係為主，稱為Extended 9D-SPA (9-Direction SPanning Area)影像表示法。NOAR能精確地表示物件之間的空間關係且提供精細的視覺化及有效的空間推理功能。以NOAR表示法為基礎，我們進而提出可用於評估任兩張影像間相似度的衡量尺度方法，並以一些例子來驗證NOAR影像表示法的有效性。Extended 9D-SPA影像表示法係延伸之前所提出的9D-SPA表示法，具有更精確的影像區別能力及彈性度。此方法可提供不同程度的空間推理，在影像擷取方面則提出十二種影像相似度的比對標準，以不同的彈性度來滿足使用者之各種需求。在3600張圖形資料庫實驗系統中，系統可以同時達到86.1％的準確率(precision)及81.2％的召回度(recall)。
In this dissertation, two image representation methods for Content-Based Image Retrieval are proposed. The first image representation method is called NOAR (Normalized Object Area Representation), which can capture the shapes and locations, as well as orientations of objects in an image. Image information retrieval systems with important functions such as spatial reasoning, visualization, browsing, and similarity retrieval can be easily built based on NOAR. The effectiveness of NOAR was demonstrated by several examples. The second image representation method is called Extended 9D-SPA, which is an extension of 9D-SPA. This method can provide different degrees of granularity for reasoning about directional relations in both eight- and sixteen-direction reference frames. In similarity retrieval, it provides twelve types of similarity measures to support flexible matching between the query picture and the database pictures. By exercising a database containing 3600 pictures, we successfully demonstrated the effectiveness of our image retrieval system based on Extended 9D-SPA. Experiment result showed that 86.1% precision rate and 81.2% recall rate can be achieved simultaneously. This performance is considered to be very good as an effective information retrieval system.
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