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2005 | 15 | 4 | 471-480
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Image retrieval based on hierarchical Gabor filters

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Content Based Image Retrieval (CBIR) is now a widely investigated issue that aims at allowing users of multimedia information systems to automatically retrieve images coherent with a sample image. A way to achieve this goal is the computation of image features such as the color, texture, shape, and position of objects within images, and the use of those features as query terms. We propose to use Gabor filtration properties in order to find such appropriate features. The article presents multichannel Gabor filtering and a hierarchical image representation. Then a salient (characteristic) point detection algorithm is presented so that texture parameters are computed only in a neighborhood of salient points. We use Gabor texture features as image content descriptors and efficiently emply them to retrieve images.
Opis fizyczny
  • Institute of Telecommunications, University of Technology and Agriculture, ul. Kaliskiego 7, 85-796 Bydgoszcz, Poland
  • Institute of Telecommunications, University of Technology and Agriculture, ul. Kaliskiego 7, 85-796 Bydgoszcz, Poland
  • Andrysiak T. and Choraś M. (2003): Hierarchical object recognition using Gabor wavelets. - Proc. Comput. Recogn. Syst., KOSYR,Miłków, Poland, pp. 271-278.
  • Bigun J. and du Buf J.M.H. (1994): N-folded symmetries by complex moments in Gabor space. - IEEE Trans. Pattern Anal. Mach. Intell., Vol. 16,No. 1, pp. 80-87.
  • Bigun J. and du Buf J.M.H. (1995): Symmetry interpretation of complex moments and the local power spectrum. - Vis. Commun. Image Represent.,Vol. 6, No 2, pp. 154-163.
  • Chen Y. and Wang J.Z. (2002): A region-based fuzzy feature matching approach to content-based image retrieval. - IEEE Trans. Pattern Anal. Machine Intell., Vol. 24, No. 9, pp. 1252-1269.
  • Choraś R. (2003): Content-based retrieval using color, texture, and shape information, In: Progress in Pattern Recognition, Speech and Image Analysis (Alberto Sanfeliu, Jose Ruiz-Shulcloper, Eds.). - Berlin: Springer, pp. 619-626.
  • Choraś R. (2004): Fuzzy processing technique for content based image retrieval, In: Artificial Intelligence and Soft Computing (L. Rutkowski et al., Eds.). - Springer, LNAI, Vol. 3070, pp. 448-451.
  • Choraś R., Andrysiak T. and Choraś M. (2005): Content based image retrieval technique, In: Computer Recognition Systems (M. Kurzynski et al., Eds.). - Springer, pp. 371-379.
  • Coggins J.M. and Jain A.K. (1985): A spatial texture approach to texture analysis. - Pattern Recogn. Lett., Vol. 3, No. 7, pp. 195-203.
  • Conners R. and Harlow C. (1980): A theoretical comparison of texture algorithms. - IEEE Trans. Pattern Anal. Mach. Intell., Vol. 2, No. 3, pp. 204-222.
  • Daugman J.G. (1985): Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. - J. Opt. Soc. Amer. A, Vol. 2, No 7, pp. 1160-1169.
  • Daugman J.G. (1988): Complete Discrete 2D Gabor Transforms by Neural Networks for Image Analysis and Compression. - IEEE Trans. Acoust., Speech Signal Process., Vol. 36, No. 7, pp. 1169-1179.
  • Daugman J.G. (1998): Recognizing persons by their iris patterns, In:Biometrics: Personal Identification in Networked Society (A.K. Jain,R. Bolle and S. Pankanti, Eds.).- Kluwer Academic Publishers, pp. 103-121.
  • Field D.J. (1987): Relations between the statistics of natural images and the response properties of cortical cells. - J. Optic. Soc. Amer., Vol. 4, No 12, pp. 2379-2394.
  • Fogel I. and Sagi D. (1989): Gabor filters as texture discriminator. - Biol. Cybern., Vol. 61, pp. 103-113.
  • Gabor D. (1946): Theory of communication. - J. Instit. Electr. Eng., Vol. 93, pp. 429-457.
  • Hammamoto Y. (1999): A Gabor filter-based method for fingerprint identification, In: Intelligent Biometric Techniques in Fingerprint and Face Recognition (L.C. Jain, U. Halici et al., Eds.).- CRC Press, pp. 137-151.
  • Jain A. and Farrokhnia F. (1991): Unsupervised texture segmentation using Gabor filters. - Pattern Recogn., Vol. 24, No. 12, pp. 1167-1186.
  • Jain A., Ratha N. and Lakshmanan S. (1997): Object detection using Gabor filters. - Pattern Recogn., Vol. 30, No 2, pp. 295-309.
  • Kruizinga P. and Petkov N. (1999): Non-linear operator for oriented texture. - IEEE Trans. Image Process., Vol. 8, No. 10, pp. 1395-1407.
  • Kruizinga P., Petkov N. and Grigorescu S.E. (1999): Comparison of texture features based on Gabor filters. - Proc. Int. Conf. ImageAnalysis and Processing, IAP, Venice, Italy, pp. 142-147.
  • Lee T. (1996): Image representation using 2D Gabor wavelets. - IEEE Trans. Pattern Anal. Mach. Intell., Vol. 18, No. 10, pp. 959-971.
  • Liu C. and Wechsler H. (2001): A Gabor feature classifier for face recognition. - Proc. IEEE Int. Conf. Computer Vision, Vancouver, Canada, pp. 270-275.
  • Ma W.Y. and Manjunath B.S. (1996): Texture Features and Learning Similarity. - Proc. IEEE Conf. Computer Vision and Pattern Recognition, San Francisco, USA, pp. 425-430.
  • Malik J. and Perona P. (1990): Preattentive texture discrimination with early vision mechanisms. - J. Optic. Soc. Amer., A, Vol. 7, No 5, pp. 923-932.
  • Manjunath B.S. and Ma W.Y. (1996): Texture Features for Browsing and Retrieval of Image Data. - IEEE Trans. Pattern Anal.Mach. Intell., Vol. 18, No 8, pp. 837-842.
  • Marcelja S. (1980): Mathematical description of the responses of simple cortical cells. - J. Optic. Soc. Amer., Vol. 2, No 7, pp. 1297-1300.
  • Mehrotra R., Namuduri K. and Ranganathan N. (1992): Gabor filter-based edge detection. - Pattern Recogn., Vol. 25, No 12, pp. 1479-1494.
  • Namuduri K.R, Mehrotra R. and Ranganathan N. (1994): Efficient computation of Gabor filter based multiresolution responses. - Pattern Recogn., Vol. 27, No 7, pp. 925-938.
  • Petkov N. and Kruizinga P. (1997): Computational models of visual neurons specialised in the detection of periodic and aperiodic oriented visual stimuli: Bar and grating cells. - Biolog. Cybern., Vol. 76, No 2, pp. 83-96.
  • Petkov N. (1995): Biologically motivated computationally intensive approaches to image pattern recognition. - Future Gener. Comput. Syst., Vol. 11, pp. 451-465.
  • Porat M. and Zeevi Y.Y. (1988): The generalized Gabor scheme of image representation in biological and machine vision. - IEEE Trans.Pattern Anal. Mach. Intell., Vol. 10, No 4, pp. 452-468.
  • Smeulders A.W.M., Worring M., Gupta A. and Jain R. (2000): Content-based image retrieval at the end of the early years. - IEEE Trans. Pattern Anal. Mach. Intell., Vol. 22, No. 12, pp. 1349-1380.
  • Spitzer H. and Hochstei S. (1985): A complex-cell receptive-field model. -J. Neurosci., Vol. 53, No. 5, pp. 1266-1286.
  • Su Y.M. and Wang J.F. (2003): A novel stroke extraction method for Chinese characters using Gabor filters. - Pattern Recogn., Vol. 36, No. 3, pp. 635-647.
  • Turner M.R. (1990): Texture discrimination by Gabor functions. - Biolog. Cybern., Vol. 55, No 1, pp. 55-73.
  • Weldon T.P., Higgins W.E. and Dunn D.F. (1996): Efficient Gabor filter design for texture segmentation. - Pattern Recogn., Vol. 29, No. 12, pp. 2005-2015.
  • Wiskott L., Fellous J.M., Kruger N. and Malsburg C.V.D. (1997): Face recognition by elastic bunch graph matching. - IEEE Trans. Pattern Anal. Mach. Intell., Vol. 19, No. 7, pp. 775-779.
  • Young I.T, Vliet van L.J. and Ginkel van M. (2002): Recursive Gabor filtering. - IEEE Trans. Signal Process., Vol. 50, No. 11.
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