Content-Based Retrieval Using Color, Texture, and Shape Information
Part of the
Lecture Notes in Computer Science
book series (LNCS, volume 2905)
Current technology allows the acquisition, transmission, storing, and manipulation of large collections of images. A way to achieve this goal is the automatic computation of features such as color, texture, shape, and position of objects within images, and the use of the features as query terms.
In this paper we describe some results of a study on similarity evaluation in image retrieval using shape, texture, color and object orientation and relative position as content features. A simple system is also introduced that computes the feature descriptors and performs queries.
KeywordsFeature Vector Image Retrieval Query Image Query Term Automatic Computation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Lew, M.S. (ed.): Principles of Visual Information Retrieval. Springer, London (2001)MATHGoogle Scholar
Swain, M.J., Ballard, D.H.: Color Indexing. International Journal of Computer Vision 7(1), 11–32 (1991)CrossRefGoogle Scholar
Drimbarean, A., Whelan, P.F.: Experiments in colour texture analysis. Pattern Recognition Letters 22, 1161–1167 (2001)MATHCrossRefGoogle Scholar
Gevers, T., Smeulders, A.W.M.: Colour based object recognition. Pattern Recognition 32, 453–464 (1999)CrossRefGoogle Scholar
Haley, G.M., Manjunath, B.S.: Rotation-Invariant texture classification using a complete space-frequency model. IEEE Transactions on Image Processing 8(2), 255–269 (1999)CrossRefGoogle Scholar
Bovik, A., Clark, M., Geisler, W.: Multichannel texture analysis using localized spatial filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(1), 55–73 (1990)CrossRefGoogle Scholar
Jain, A.K., Farrokhnia, F.: Unsupervised texture segmentation using Gabor filters. Pattern Recognition 24(12), 1167–1186 (1991)CrossRefGoogle Scholar
Manjunath, B.S., Ma, W.Y.: Texture features for browsing and retrieval of data. IEEE Trans. Pattern Analysis Machine Intelligence 18(8), 837–842 (1996)CrossRefGoogle Scholar
Mokhtarian, F., Mackworth, A.: Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(1), 34–43 (1986)CrossRefGoogle Scholar
Persoon, E., Fu, K.S.: Shape Discrimination Using Fourier Descriptors. IEEE Trans. On Systems, Man and Cybernetics SMC-7(3), 170–179 (1977)MathSciNetCrossRefGoogle Scholar
Hu, M.: Visual pattern recognition by moment invariants. IEEE Trans. on Inf. Theory 8, 179–187 (1962)Google Scholar
Hu, R.T.: The revised fundamental theorem of moment invariants. IEEE Transactions on Pattern Analysis and Machine Intelligence 13, 830–834 (1991)CrossRefGoogle Scholar
Tan, T.N.: Rotation Invariant Texture Features and Their Use in Automatic Script Identification. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(7), 751–756 (1998)CrossRefGoogle Scholar
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