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Tytuł artykułu

An Image Retrieval System Based on the Color, Areas, and Perimeters of Objects

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Two different objects can be generally distinguished by their colors, areas, and perimeters. This paper hence proposes an image retrieval system which uses the colors, areas, and perimeters of objects in an image as the features of the image. The system is insensitive to the shift and rotation variations of objects in images, as well as to the scale and noise variations of images. The experimental results show that this system is capable of recognizing different images very well.
Wydawca
Rocznik
Strony
319--330
Opis fizyczny
fot., wykr., bibliogr. 18 poz.
Twórcy
autor
autor
autor
autor
autor
  • Department of Management Information System, National Chung Hsing University, 250 Kaokuang, Road, 402 Taichung, Taiwan, R.O.C., clwang, rhhwang@cs.ccu.edu.tw
Bibliografia
  • [1] Adoram, M., Lew, M. S.: IRUS: Image retrieval using shape, IEEE International Conference on Multimedia Computing and System, 2, 1999, 597-602.
  • [2] Brunelli, R., Mich, O.: Histograms analysis for image retrieval, Pattern Recognition, 34, 2001, 1625-1637.
  • [3] Chan, Y. K., Chang, C. C.: A color image retrieval system based on the run-length representation, Pattern Recognition Letter, 22, 2001, 447-455.
  • [4] Chang, C. C., Chan, Y. K.: A fast filter for image retrieval based on color-spatial features, SEMA 2000, Baden-Baden, German, July 2000, 47-51.
  • [5] Chan, T., Chen, L. H.: Fast mapping algorithm for histogram to binary set conversion, Pattern Recognition Letter, 21, 2000, 899-906.
  • [6] Dimai, A.: Differences of global features for region indexing, The Technical Report 177 of Swiss Federal Institute of Technology Lausanne, 1997.
  • [7] Dunn, J. C.: A fuzzy relative of the ISODATA process and its use in detecting compact, well separated clusters, Journal Cybernet, 3(3), March 1974, 32-57.
  • [8] Eukunaga, K,: Introduction to statistical pattern recognition, San Diego, CA., Academic Press, 1990.
  • [9] Gudivada, V. N., Raghavan, V. V.: Design and evaluation of algorithms for image retrieval by spatial similarity, ACM Transactions on Information System, 13(2) , April 1995, 115-144.
  • [10] Huang, P. W., Jean, Y. R.: Spatial reasoning and similarity retrieval for image database system based on RS-string, Pattern Recognition, 29(12), 1996, 2103-2114.
  • [11] Ju, H., Ma, K. K.: Fuzzy color histogram and its use in color image retrieval, IEEE Transactions on Image Processing, 11(8), 2002, 944-952.
  • [12] Manjunath, B. S., Ohm, J. R., Vasudevan, V. V., Yamada, A.: Color and texture descriptors, IEEE Transactions on Circuits and Systems for Video Technology, 11(6), June 2001, 703-715.
  • [13] Sawhney, H. S., Hafner, J. L.: Efficient color histogram indexing, Proceedings of IEEE International Conference on Image Processing, 2, Austin, Texas, November 1994, 66-77.
  • [14] Shearer, K., Venkatesh, S., Kieronska, D.: Spatial indexing for video databases, Journal of Visual Communication and Image representation, 7(4), 1996, 325-335.
  • [15] Stricker, M., Orengo, M.: Similarity of color images, Proceedings of SPIE - storage and retrieval for image and video databases III, 2420, San Diego/La Jolla, CA, USA, February 1995, 381-392.
  • [16] Stricker, M, Swan, M.: The capacity of color histogram indexing, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Seattle, Washington, June 1994, 704-708.
  • [17] Su, M. C., Chou, C. H.: A modified version of the K-means algorithm with a distance based on cluster symmetry, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6), June 2001, 674-680.
  • [18] ISO/IEC JTC1/SC29/WG11/N4063, MPEG-7 Visual Part of Experimentation Model Version 10.0, Singapore, March 2001.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS2-0009-0039
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