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A Multistep Approach for Shape Similarity Search in Image Databases
November/December 1998 (vol. 10 no. 6)
pp. 996-1004

Abstract—Shape similarity search is a crucial task in image databases, particularly in the presence of errors induced by segmentation or scanning images. The resulting slight displacements or rotations have not been considered so far in the literature. We present a new similarity model that flexibly addresses this problem. By specifying neighborhood influence weights, the user may adapt the similarity distance functions to her or his requirements or preferences. Technically, the new similarity model is based on quadratic forms for which we present a multistep query processing architecture particularly for high dimensions as they occur in image databases. Our algorithm to reduce the dimensionality of quadratic form-based similarity queries results in a lower-bounding distance function that is proven to provide an optimal filter selectivity. Experiments on our test database of 10,000 images demonstrate the applicability and the performance of our approach even in high dimensions such as 1,024.

[1] M. Ankerst, B. Braunmeller, H.-P. Kriegel, and T. Seidl, “Improving Adaptable Similarity Query Processing by Using Approximations,” Proc. 24th Int'l Conf. Very Large Data Bases (VLDB), 1998.
[2] S. Berchtold, C. Böhm, and H.-P. Kriegel, “A Cost Model for Nearest Neighbor Search in High-Dimensional Data Spaces,” Proc. 16th ACM SIGACT-SIGMOD-SIGART Symp. Principles of Database Systems (PODS), pp. 78-86, 1997.
[3] S. Berchtold, C. Böhm, B. Braunmüller, D. Keim, and H.-P. Kriegel, “Fast Parallel Similarity Search in Multimedia Databases,” Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 1-12, 1997.
[4] S. Berchtold, D. Keim, and H.-P. Kriegel, “The X-Tree: An Index Structure for High-Dimensional Data,” Proc. 22nd Conf. Very Large Data Bases, pp. 28-39, 1996.
[5] P.J. Besl and N.D. McKay, "A Method for Registration of 3D Shapes," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, Feb. 1992.
[6] T. Bozkaya and M. Ozsoyoglu, “Distance-Based Indexing for High-Dimensional Metric Spaces,” Proc. SIGMOD Int'l Conf. Management of Data, pp. 357-368, 1997.
[7] P. Ciaccia, M. Patella, and P. Zezula, “M-Tree: An Efficient Access Method for Similarity Search in Metric Spaces,” Proc. Int'l Conf. Very Large Data Bases, 1997.
[8] C. Faloutsos, R. Barber, M. Flicker, J. Hafner, W. Niblack, and W. Equitz, "Efficient and effective querying by image content," J. Intell. Information Systems," vol. 3, pp. 231-262, 1994.
[9] C. Faloutsos and K.I. Lin, “Fastmap: A Fast Algorithm for Indexing, Data-Mining and Visualization of Traditional and Multimedia Datasets,” Proc. SIGMOD, Int'l Conf. Management of Data, pp. 163-174, 1995.
[10] C. Faloutsos, M. Ranganathan, and I. Manolopoulos, “Fast Subsequence Matching in Time Series Databases,” Proc. ACM SIGMOD, pp. 419-429, May 1994.
[11] J.E. Gary and R. Mehrotra, "Similar Shape Retrieval Using a Structural Feature Index," Information Systems, vol. 18, no. 7, pp. 525-537, 1993.
[12] J. Hafner, H.S. Sawhney, W. Equitz, M. Flickner, and W. Niblack, “Efficient Color Histogram Indexing for Quadratic Form Distance Functions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 7, pp. 729-736, July 1995.
[13] A. Henrich, "A Distance-Scan Algorithm for Spatial Access Structures," Proc. Second ACM Workshop Advances in Geographic Information Systems,Gaithersburg, Md., pp. 136-143, 1994.
[14] G.R. Hjaltason and H. Samet, “Ranking in Spatial Databases,” Proc. Fourth Int'l Symp. Large Spatial Databases, pp. 83-95, 1995.
[15] H.V. Jagadish, “A Retrieval Technique for Similar Shapes,” Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 208-217, 1991.
[16] F. Korn, N. Sidiropoulos, C. Faloutsos, E. Siegel, and Z. Protopapas, “Fast Nearest-Neighbor Search in Medical Image Databases,” Proc. Conf. Very Large Data Bases (VLDB '96), Sept. 1996.
[17] H.-P. Kriegel and T. Seidl, "Approximation-Based Similarity Search for 3-D Surface Segments," GeoInformatica J., Kluwer Academic, vol. 2, no. 2, pp. 113-147, 1998.
[18] H.P. Kriegel, T. Schmidt, and T. Seidl, "3D Similarity Search by Shape Approximation," Proc. Fifth Int'l Symp. Large Spatial Databases (SSD'97),Berlin, Germany, Lecture Notes in Computer Science, vol. 1,262, pp.11-28, 1997.
[19] J.B. Kruskal and M. Wish, "Multidimensional Scaling," SAGE, Beverly Hills, Calif., 1978.
[20] K. Lin, H.V. Jagadish, and C. Faloutsos, “The TV-Tree: An Index Structure for High-Dimensional Data,” VLDB J., vol. 3, pp. 517-542, 1995.
[21] W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glasmann, D. Petkovic, P. Yanker, C. Faloutsos, and G. Taubin, "The QBIC Project: Querying Images by Content Using Color, Texture, and Shape," PIE 1993 Int'l Symp. Electronic Imaging: Science and Technology Conf. 1908, Storage and Retrieval for Image and Video Databases,San Jose, Calif., 1993.
[22] N. Roussopoulos, S. Kelley, and F. Vincent, “Nearest Neighbor Queries,” Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 71-79, 1995.
[23] T. Seidl, "Adaptable Similarity Search in 3-D Spatial Database Systems," PhD thesis, Inst. for Computer Science, Univ. of Munich, 1997; Herbert Utz Publishers, Munich, Germany, http:/utzverlag.com
[24] H. Sawhney and J. Hafner, “Efficient Color Histogram Indexing,” Proc. Int'l Conf. Image Processing, pp. 66-70, 1994.
[25] T. Seidl and H.-P. Kriegel, "Efficient User-Adaptable Similarity Search in Large Multimedia Databases," Proc. 23rd VLDB Conf., pp. 506-515,Athens, Aug. 1997.
[26] T. Seidl and H.-P. Kriegel, “Optimal Multi-Step k-Nearest Neighbor Search,” Proc. ACM SIGMOD Int'l Conf. Management of Data, pp. 154-165, 1998.
[27] G. Taubin and D.B. Cooper, "Recognition and Positioning of Rigid Objects Using Algebraic Moment Invariants," Geometric Methods in Computer Vision, vol. 1,570, pp. 175-186, SPIE, 1991.
[28] D. White and R. Jain, “Similarity Indexing with the SS-Tree,” Proc. 12th Int'l Conf. Data Eng., 1996.

Index Terms:
Content-based image retrieval, adaptable similarity search, multistep query processing, searching and browsing large image databases, managing high-dimensional image data.
Citation:
Mihael Ankerst, Hans-Peter Kriegel, Thomas Seidl, "A Multistep Approach for Shape Similarity Search in Image Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 10, no. 6, pp. 996-1004, Nov.-Dec. 1998, doi:10.1109/69.738362
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