A System Supporting Semantics Retrieval

With the advance of multimedia technology, image data in various formats are becoming available at an explosive rate. With such enormous data resources, the search and retrieval of image databases are demanded to provide open access to relevant information and products. Thus, content-based image retrieval (CBIR) has become an active research area. A variety of techniques have been developed. In particular, content-based image retrieval using low-level features such as colour [36, 34, 26], texture [21, 33, 32, 20], shape [22, 14, 23, 24, 15, 10, 17] and others [30, 2, 16, 7] extracted from the images has been well studied. Various image querying systems including QBIC [11], VisualSeek [34], PhotoBook [27] and Virage [5] have been built based on the low-level features for general or specific image retrieval tasks.

[1]  Narendra Ahuja,et al.  Dot Pattern Processing Using Voronoi Neighborhoods , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Rosalind W. Picard.  A Society of Models for Video and Image Libraries , 1996, IBM Syst. J..

[3]  Josef Kittler,et al.  Robust and Efficient Shape Indexing through Curvature Scale Space , 1996, BMVC.

[4]  James W. Modestino,et al.  Texture Discrimination Based Upon an Assumed Stochastic Texture Model , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[6]  Christos Faloutsos,et al.  Efficient and effective Querying by Image Content , 1994, Journal of Intelligent Information Systems.

[7]  Antonio Torralba,et al.  Semantic organization of scenes using discriminant structural templates , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[8]  James L. Crowley,et al.  A Representation for Shape Based on Peaks and Ridges in the Difference of Low-Pass Transform , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.

[10]  Stephen P. Morse,et al.  Concepts of use in contour map processing , 1969, Commun. ACM.

[11]  Shih-Fu Chang,et al.  Transform features for texture classification and discrimination in large image databases , 1994, Proceedings of 1st International Conference on Image Processing.

[12]  Christos Faloutsos,et al.  Fast Nearest Neighbor Search in Medical Image Databases , 1996, VLDB.

[13]  Azriel Rosenfeld,et al.  Mosaic Models for Textures , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Berthold K. P. Horn.  Robot vision , 1986, MIT electrical engineering and computer science series.

[15]  Steve McLaughlin,et al.  Comparative study of textural analysis techniques to characterise tissue from intravascular ultrasound , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[16]  Narendra Ahuja,et al.  Unsupervised multidimensional hierarchical clustering , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[17]  Charles T. Zahn,et al.  Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters , 1971, IEEE Transactions on Computers.

[18]  Ramin Zabih,et al.  Comparing images using color coherence vectors , 1997, MULTIMEDIA '96.

[19]  Shih-Fu Chang,et al.  VisualSEEk: a fully automated content-based image query system , 1997, MULTIMEDIA '96.

[20]  B. S. Manjunath,et al.  NeTra: A toolbox for navigating large image databases , 1997, Multimedia Systems.

[21]  John P. Eakins,et al.  Automatic image content retrieval - are we getting anywhere? , 2002 .

[22]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Arun K. Sood,et al.  Selecting image subbands for browsing scientific image databases , 1994, Defense, Security, and Sensing.

[24]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[25]  Aidong Zhang,et al.  Approach to clustering large visual databases using wavelet transform , 1997, Electronic Imaging.

[26]  Hayit Greenspan,et al.  Finding Pictures of Objects in Large Collections of Images , 1996, Object Representation in Computer Vision.

[27]  Aidong Zhang,et al.  Monotonic Tree of Images and Its Application in Image Processing , 2001 .

[28]  Narendra Ahuja,et al.  Extraction of early perceptual structure in dot patterns: Integrating region, boundary, and component gestalt , 1989, Comput. Vis. Graph. Image Process..

[29]  Amarnath Gupta,et al.  Virage image search engine: an open framework for image management , 1996, Electronic Imaging.

[30]  Alex Pentland,et al.  Photobook: Content-based manipulation of image databases , 1996, International Journal of Computer Vision.

[31]  Josef Kittler,et al.  Efficient and Robust Retrieval by Shape Content through Curvature Scale Space , 1998, Image Databases and Multi-Media Search.

[32]  Rajiv Mehrotra,et al.  Similar-Shape Retrieval in Shape Data Management , 1995, Computer.

[33]  T. Kato,et al.  Rough sketch-based image information retrieval , 1993 .