This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Knowledge-Based Approach for Retrieving Images by Content
August 1996 (vol. 8 no. 4)
pp. 522-532

Abstract—A knowledge-based approach is introduced for retrieving images by content. It supports the answering of conceptual image queries involving similar-to predicates, spatial semantic operators, and references to conceptual terms. Interested objects in the images are represented by contours segmented from images. Image content such as shapes and spatial relationships are derived from object contours according to domain-specific image knowledge. A three-layered model is proposed for integrating image representations, extracted image features, and image semantics. With such a model, images can be retrieved based on the features and content specified in the queries. The knowledge-based query processing is based on a query relaxation technique. The image features are classified by an automatic clustering algorithm and represented by Type Abstraction Hierarchies (TAHs) for knowledge-based query processing. Since the features selected for TAH generation are based on context and user profile, and the TAHs can be generated automatically by a clustering algorithm from the feature database, our proposed image retrieval approach is scalable and context-sensitive. The performance of the proposed knowledge-based query processing is also discussed.

[1] J.R. Bach, S. Paul, and R. Jain, “A Visual Information Management System for the Interactive Retrieval of Faces,” IEEE Trans. Knowledge and Data Eng., vol. 5, no. 4, pp. 619-628, 1993.
[2] M.S. Brown, R.W. Gill, H.E. Talhami, L. Wilson, and D.B. Doust, "Model-Based Assessment of Lung Structures: Inferencing and Control System," Proc. SPIE, vol. 2,433, pp. 167-178, 1995.
[3] "The Object Database Standard: ODMG—93, Release 1.2," R.G.G. Cattell, ed. Morgan Kaufmann, 1996.
[4] S.K. Chang, C.W. Yan, D.C. Dimitroff, and T. Arndt, “An Intelligent Image Database System,” IEEE Trans. Software Eng., vol. 14, no. 5, pp. 681-688, May 1988.
[5] W.E. Chu and Q. Chen, “A Structured Approach for Cooperative Query Answering,” IEEE Trans. Knowledge and Data Engineering, Vol. 6 No. 5 Oct. 1994, pp. 738–749.
[6] W.W. Chu and K. Chiang, "Abstraction of High Level Concepts from Numerical Values in Databases," Proc. AAAI Workshop Knowledge Discovery in Databases, July 1994.
[7] W.W. Chu, T. Ieong, and R. Taira, "A Semantic Modeling Approach for Image Retrieval by Content," VLDB J., vol. 3, no. 4,445-478, Oct. 1994.
[8] W.W. Chu, M.A. Merzbacher, and L. Berkovich, “The Design and Implementation of CoBase,” SIGMOD Record, vol. 22, no. 2, pp. 517-522, June 1993.
[9] W. Chu, H. Yang, K. Chiang, M. Minock, G. Chow, and C. Larson, “Cobase: A Scalable and Extensible Cooperative Information System,” J. Intelligent Information Systems, vol. 6, pp. 223-259, May 1996.
[10] W.W. Chu, H. Yang, K. Chiang, B. Ribeiro, and G. Chow, "CoGIS: A Cooperative Geographical Information System," Proc. SPIE Conf. Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry,Orlando, Fla., Apr. 1994.
[11] W.W. Chu, A.F. Cárdenas, and R.K. Taira, "KMeD: A Knowledge-Based Multimedia Medical Distributed Database System," Information Systems, vol. 20, no. 2, pp. 75-96, 1995.
[12] D. Daneels et al., "Interactive Outlining: An Improved Approach Using Active Contours," Image and Video Storage and Retrieval, SPIE, 1993.
[13] M. Egenhofer, “Reasoning about Binary Topological Relations,” Proc. Second Symp. Large Spatial Databases, O. Gunther and H. J. Schek, eds., pp. 143–160, 1991.
[14] I. Kapouleas, "Segmentation and Feature Extraction for Magnetic Resonance Brain Image Analysis," Proc. 10th Int'l Conf. Pattern Recognition, pp. 583-590, 1990.
[15] M.D. Levine, "Vision in Man and Machine," McGraw Hill, 1985.
[16] W.N. Martin and J.K. Aggarwal, "Computer Analysis of Dynamic Scenes Containing Currilinear Figures," Pattern Recognition, vol. 11, pp. 169-178, 1979.
[17] R. Mehrotra and J.E. Gary, “Similar-Shape Retrieval in Shape Data Management,” Computer, vol. 28, no. 9, pp. 57-62, Sept. 1995.
[18] W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glasman, D. Petkovic, P. Yanker, C. Faloutsos, and G. Taubin, "The QBIC Project: Querying Images by Content Using Color, Texture, and Shape," Storage and Retrieval for Images and Video Databases, SPIE, 1993.
[19] W.A. Perkins, "A Model-based Vision System for Industrial Parts," IEEE Trans. Computers, vol. 27, no. 2, Feb. 1978.
[20] J. Qian, T. Mitsa, G. Sudaramoorthy, and E.A. Hoffman, "3D Bronchial Tree Model and Fractal Analysis as Tools for Performance Evaluation of Different ct Acquisition/Reconstruction Schemes," Proc. SPIE, vol. 2,433, pp. 113-120, 1995.
[21] F. Rabitti and P. Savino, “An Information Retrieval Approach for Image Databases,” Proc. 18th VLDB, pp. 574–584, 1992.
[22] M. Sonka, V. Hlavac, and R. Boyle, Image, Processing, Analysis, and Machine Vision, vol. 1. Chapman and Hall Computing, 1993.
[23] M. Sonka, W. Park, and E.A. Hoffman, "Validation of an Enhanced Knowledge-Based Method for Segmentation and Quantitative Analysis of Intrathoracic Airway Trees from Three-Dimensional ct Images," Proc. SPIE, vol. 2,433, pp. 158-166, 1995.
[24] R. Wasserman et al., "Multimodality Tumor Delineation Via Fuzzy Fusion and Deformable Modelling," Proc. SPIE, Medical Image: Image Processing, 1995.
[25] A.J. Worth, S. Lehar, and D.N. Kennedy, "A Recurrent Cooperative/Competitive Field for Segmentation of Magnetic Resonance Brain Images," IEEE Trans. Knowledge and Data Eng., vol. 4, no. 2, pp. 156-161, Apr. 1992.

Index Terms:
Knowledge-based query processing, medical Image database, retrieve image by feature and content, spatial query processing, knowledge-based spatial image model, cooperative query processing, shape model, spatial relationship model.
Citation:
Chih-Cheng Hsu, Wesley W. Chu, Ricky K. Taira, "A Knowledge-Based Approach for Retrieving Images by Content," IEEE Transactions on Knowledge and Data Engineering, vol. 8, no. 4, pp. 522-532, Aug. 1996, doi:10.1109/69.536245
Usage of this product signifies your acceptance of the Terms of Use.