Publication 2006 Issue No. 10 - October Abstract - An Effective and Efficient Exact Match Retrieval Scheme for Symbolic Image Database Systems Based on Spatial Reasoning: A Logarithmic Search Time Approach
An Effective and Efficient Exact Match Retrieval Scheme for Symbolic Image Database Systems Based on Spatial Reasoning: A Logarithmic Search Time Approach
October 2006 (vol. 18 no. 10)
pp. 1368-1381
 ASCII Text x P. Punitha, D.S. Guru, "An Effective and Efficient Exact Match Retrieval Scheme for Symbolic Image Database Systems Based on Spatial Reasoning: A Logarithmic Search Time Approach," IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 10, pp. 1368-1381, October, 2006.
 BibTex x @article{ 10.1109/TKDE.2006.154,author = {P. Punitha and D.S. Guru},title = {An Effective and Efficient Exact Match Retrieval Scheme for Symbolic Image Database Systems Based on Spatial Reasoning: A Logarithmic Search Time Approach},journal ={IEEE Transactions on Knowledge and Data Engineering},volume = {18},number = {10},issn = {1041-4347},year = {2006},pages = {1368-1381},doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2006.154},publisher = {IEEE Computer Society},address = {Los Alamitos, CA, USA},}
 RefWorks Procite/RefMan/Endnote x TY - JOURJO - IEEE Transactions on Knowledge and Data EngineeringTI - An Effective and Efficient Exact Match Retrieval Scheme for Symbolic Image Database Systems Based on Spatial Reasoning: A Logarithmic Search Time ApproachIS - 10SN - 1041-4347SP1368EP1381EPD - 1368-1381A1 - P. Punitha, A1 - D.S. Guru, PY - 2006KW - Exact match retrievalKW - direction of referenceKW - modified binary searchKW - spatial relationshipKW - symbolic imageKW - symbolic image database.VL - 18JA - IEEE Transactions on Knowledge and Data EngineeringER -
In this paper, a novel method of representing symbolic images in a symbolic image database (SID) invariant to image transformations that is useful for exact match retrieval is presented. The relative spatial relationships existing among the components present in an image are perceived with respect to the direction of reference [15] and preserved by a set of triples. A distinct and unique key is computed for each distinct triple. The mean and standard deviation of the set of keys computed for a symbolic image are stored along with the total number of keys as the representatives of the corresponding image. The proposed exact match retrieval scheme is based on a modified binary search technique and, thus, requires O(log n) search time in the worst case, where n is the total number of symbolic images in the SID. An extensive experimentation on a large database of 22,630 symbolic images is conducted to corroborate the superiority of the model. The effectiveness of the proposed representation scheme is tested with standard testbed images.

[1] V.N. Gudivada, “$\Theta {\rm{R}}{\hbox{-}}\rm string$ : A Geometry-Based Representation for Efficient and Effective Retrieval of Images by Spatial Similarity,” IEEE Trans. Knowledge and Data Eng., vol. 10, no. 3, pp. 504-512, May/June 1998.
[2] D. Maltoni, D. Maio, A.J. Jain, and S. Prabhakar, Handbook of Fingerprint Recognition. Springer Professional Computing, 2005.
[3] S.C. Orphanoudakis, C. Chronaki, and S. Kostomanolakis, “I2C: A System for the Indexing, Storage and Retrieval of Medical Images by Content,” J. Medical Informatics, vol. 19, no. 2, pp. 109-122, 1994.
[4] E.G.M. Petrakis and C. Faloustsos, “Similarity Searching in Medical Image Databases,” IEEE Trans. Knowledge and Data Eng., vol. 9, no. 3, pp. 435-447, 1997.
[5] S.K. Chang, Q.Y. Shi, and C.W. Yan, “Iconic Indexing by 2D Strings,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 5, pp. 413-428, Sept. 1987.
[6] S.K. Chang, E. Jungert, and Y. Li, “Representation and Retrieval of Symbolic Pictures Using Generalized 2D Strings,” SPIE Proc. Conf. Visual Comm. and Image Processing, pp. 1360-1372, 1989.
[7] C.C. Chang and T.C. Wu, “Retrieving the Most Similar Symbolic Pictures from Pictorial Databases,” Information Processing and Management, vol. 28, no. 5, pp. 581-588, 1992.
[8] T.C. Wu and C.C. Chang, “Application of Geometric Hashing to Iconic Database Retrieval,” Pattern Recognition Letters, vol. 15, pp. 871-876, 1994.
[9] P.W. Huang and Y.R. Jean, “Using 2D C+ Strings as Spatial Knowledge Representation for Image Database Systems,” Pattern Recognition, vol. 27, no. 9, pp. 1249-1257, 1994.
[10] X.M. Zhou and C.H. Ang, “Retrieving Similar Pictures from Pictorial Database by an Improved Hashing Table,” Pattern Recognition Letters, vol. 18, pp. 751-758, 1997.
[11] X.M. Zhou, C.H. Ang, and T.W. Ling, “Image Retrieval Based on Object's Orientation Spatial Relationship,” Pattern Recognition Letters, vol. 22, pp. 469-477, 2001.
[12] E.G.M. Petrakis and S.C. Orphanoudakis, “A Methodology for the Representation, Indexing and Retrieval of Images by Content,” Image and Vision Computing, vol. 8, no. 11, pp. 504-521, 1993.
[13] E.G.M. Petrakis, “Design and Evaluation of Spatial Similarity Approaches for Image Retrieval,” Image and Vision Computing, vol. 20, pp. 59-76, 2002.
[14] A.K. Majumdar, I. Bhattacharya, and A.K. Saha, “An Object-Oriented Fuzzy Data Model for Similarity Detection in Image Databases,” IEEE Trans. Knowledge and Data Eng., vol. 14, no. 5, pp. 1186-1189, Sept./Oct. 2002.
[15] D.S. Guru and P. Punitha, “An Invariant Scheme for Exact Match Retrieval of Symbolic Images Based Upon Principal Component Analysis,” J. Pattern Recognition Letters, vol. 25, no. 1, pp. 73-86, 2004.
[16] S.K. Chang and Y. Li, “Representation of Multi-Resolution Symbolic and Binary Pictures Using 2D H Strings,” Proc. IEEE Workshop Languages for Automata, pp. 190-195, 1988.
[17] S.Y. Lee and F.J. Hsu, “2D C String: A New Spatial Knowledge Representation for Image Database System,” Pattern Recognition, vol. 23, no. 10, pp. 1077-1087, 1990.
[18] S.Y. Lee and F.J. Hsu, “Picture Algebra for Spatial Reasoning of Iconic Images Represented in 2D C String,” Pattern Recognition Letters, vol. 12, no. 7, pp. 425-435, 1991.
[19] C.C. Chang and D.C. Lin, “A Spatial Data Representation: An Adaptive 2D H String,” Pattern Recognition Letters, vol. 17, pp. 175-185, 1996.
[20] Y.I. Chang and H.Y. Ann, “A Note On Adaptive 2D-H Strings,” Pattern Recognition Letters, vol. 20, pp. 15-20, 1999.
[21] S.Y. Lee, M.K. Shan, and W.P. Yang, “Similarity Retrieval of Iconic Image Databases,” Pattern Recognition, vol. 22, no. 6, pp. 675-682, 1989.
[22] S.Y. Lee and M.K. Shan, “Access Methods of Image Databases,” Pattern Recognition and Artificial Intelligence, vol. 4, no. 1, pp. 27-44, 1990.
[23] 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.
[24] S.K. Bhatia and C.L. Sabharwal, “A Fast Implementation of a Perfect Hash Function for Picture Objects,” Pattern Recognition, vol. 27, no. 3, pp. 365-375, 1994.
[25] C.L. Sabharwal and S.K. Bhatia, “Perfect Hash Table Algorithm for Image Databases Using Negative Associated Values,” Pattern Recognition, vol. 28, no. 7, pp. 1091-1101, 1995.
[26] C.L. Sabharwal and S.K. Bhatia, “Image Databases and Near Perfect Hash Table,” Pattern Recognition, vol. 30, no. 11, pp. 1867-1876, 1997.
[27] C.C. Chang, “Spatial Match Retrieval of Symbolic Pictures,” Information Science and Eng., vol. 7, pp. 405-422, 1991.
[28] C.C. Chang and T.C. Wu, “An Exact Match Retrieval Scheme Based upon Principal Component Analysis,” Pattern Recognition Letters, vol. 16, pp. 465-470, 1995.
[29] K. Segupta and K.L. Boyer, “Organising Large Structural Modelbases,” IEEE Trans. Pattern Recognition and Machine Intelligence, vol. 17, no. 4, pp. 321-332, Apr. 1995.
[30] B.T. Messmer and H. Bunke, “Fast Error Correcting Graph Isomorphism Based on Model Precompilation,” technical report, Univ. of Bern, Switerland, 1996.
[31] P. Korn, N. Sidiropulos, C. Faloustsos, E. Siegel, and Z. Proptopapas, “Fast and Effective Retrieval of Medical Tumor Shapes,” IEEE Trans. Knowledge and Data Eng., vol. 10, no. 6, pp. 889-904, Nov./Dec. 1998.
[32] Q. Jiang and W. Zhang, “An Improved Method for Finding Nearest Neighbors,” Pattern Recognition Letters, vol. 14, no. 7, pp. 531-535, 1993.
[33] A.K. Ghosh, P. Chaudhuri, and C.A. Murthy, “On Visualization and Aggregation of Nearest Neighbor Classifiers,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1592-1602, Oct. 2005.
[34] G. Petraglia, M. Sebillo, M. Tucci, and G. Tortora, “A Normalized Index for Image Databases,” Intelligent Image Database Systems, 1996.
[35] D.S. Guru, P. Punitha, and P. Nagabhushan, “Archival and Retrieval of Symbolic Images: An Invariant Scheme Based on Triangular Spatial Relationship,” Pattern Recognition Letters, vol. 24, no. 14, pp. 2397-2408, 2003.
[36] G. Petraglia, M. Sebillo, M. Tucci, and G. Tortora, “Virtual Images for Similarity Retrieval in Image Databases,” IEEE Trans. Knowledge and Data Eng., vol. 13, no. 6, pp. 951-967, Nov./Dec. 2001.
[37] D.E. Sciascio, M. Mongiello, F.M. Donini, and L. Allegretti, “Retrieval by Spatial Similarity: An Algorithm and Comparative Evaluation,” Pattern Recognition Letters, vol. 25, no. 14, pp. 1633-1645, 2004.
[38] D.S. Guru, H.J. Raghavendra, and M.G. Suraj, “An Adaptive Binary Search Based Sorting by Insertion: An Efficient and Simple Algorithm,” Statistics and Applications, vol. 2, pp. 85-96, 2000.
[39] D.S. Guru, “Towards Accurate Recognition of Objects Employing a Partial Knowledge Base: Some New Approaches,” PhD thesis, Dept. of Studies in Computer Science, Univ. of Mysore, Manasagangothri, Mysore, India, 2000.
[40] V.N. Gudivada and V.V. Raghavan, “Design and Evaluation of Algorithms for Image Retrieval by Spatial Similarity,” ACM Trans. Information Systems, vol. 13, no. 2, pp. 115-144, 1995.
[41] P. Bollmann, F. Jochum, U. Reiner, V. Weissmann, and H. Zuse, “The LIVE-Project-Retrieval Experiments Based on Evaluation Viewpoints,” Proc. Eighth Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR '85), pp. 213-214, 1985.
[42] R. Dinesh and D.S. Guru, “Mathematical Morphology Based Corner Detection Scheme: A Non-Parametric Approach,” Proc. Fourth Indian Conf. Computer Vision, Graphics and Image Processing (ICVGIP '04), pp. 76-81, Dec. 2004.
[43] R. Dinesh and D.S. Guru, “Corner Detection and Interpretation of Boundary Segments Useful for Production of Symbolic Images for 2D Objects,” Proc. Int'l Conf. Recent Trends in Information Systems (IRIS '06), 2006.

Index Terms:
Exact match retrieval, direction of reference, modified binary search, spatial relationship, symbolic image, symbolic image database.
Citation:
P. Punitha, D.S. Guru, "An Effective and Efficient Exact Match Retrieval Scheme for Symbolic Image Database Systems Based on Spatial Reasoning: A Logarithmic Search Time Approach," IEEE Transactions on Knowledge and Data Engineering, vol. 18, no. 10, pp. 1368-1381, Oct. 2006, doi:10.1109/TKDE.2006.154