Abstract
We propose an image indexing and retrieval method which is based on the multiscale image analysis theory in conjunction with fuzzy image feature extraction. The main idea is based on the assumption that the fundamental cues for image description such as shape and textures should be considered together within a unified model. Here the multiscale analysis is modeled by a differential morphological filter, and the feature are extracted by a multiscale fuzzy gradient operation applied to the detail images, which are the differences between images at successive scales. Experiments with large image databased and comparisons with classical methods are reported.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Alvarez, L., Guichard, F., Lions, P.L., Morel, J.M.: Axioms and fundamental equations of image processing. Archives for Rational Mechanics and Analysis 123(3), 199–257 (1993)
Apostolico, A., Caianiello, E.R., Fischetti, E., Vitulano, S.: C-Calculus: an elementary approach to some problems in pattern recognition. Pattern Recognition 19, 375–387 (1878)
Brockett, R.W., Maragos, P.: Evolution equations for continuous-scale morphological filtering. IEEE Trans. Signal Processing 42, 3377–3386 (1994)
Caianiello, E.R., Petrosino, A.: Neural networks, fuzziness and image processing. In: Cantoni, V. (ed.) Machine and Human Perception: Analogies and Divergences, pp. 355–370. Plenum Press, New York (1994)
Ceccarelli, M., Petrosino, A.: A parallel fuzzy scale-space approach to the unsupervised texture separation. Pattern Recognition Letters 23, 557–567 (2002)
Del Bimbo, A., Pala, P.: Visual Image Retrieval by Elastic Matching of User Sketches. IEEE Trans. Pattern Analysis and Machine Intelligence 19(2), 121–132 (1997)
Gnu Fundation, The GNU Image-Finding Tool, http://www.gnu.org/software/gift/gift.html
Keim, D.A., Heczko, M., Hinneburg, A.: Multi-Resolution Similarity Search in Image Databases. ACM/Springer Multimedia Systems Journal (2003)
Krishnapuram, R., Medasani, S., Jung, S.-H., Choi, Y.-S., Balasubramaniam, R.: Content-Based Image Retrieval Based on a Fuzzy Approach. IEEE Trans. on Knowledge and Data Engineering 16(10) (2004)
Koenderink, J.: The structure of images. Biological Cybernetics 5, 363–370 (1984)
Jackway, P.T., Deriche, M.: Scale-Space properties of the Multiscale Morphological Dilation-Erosion. IEEE Trans. Pattern Analysis and Machine Intelligence 18(1), 38–51 (1996)
Jain, A., Vailaya, A.: Image Retrieval Using Color and Shape. Pattern Recognition 29(8), 1233–1244 (1996)
Liu, F., Picard, R.W.: Periodicity, Directionality, and Randomness: Wold Features for Image Modeling and Retrieval. IEEE Trans. Pattern Analysis and Machine Intelligence 18(7), 722–733 (1996)
Manjunath, B.S., Ma, W.Y.: Texture Features for Browsing and Retrieval of Image Data. IEEE Trans. Pattern Analysis and Machine Intelligence 18(8), 837–842 (1996)
Mehrotra, R., Gary, J.E.: Similar-Shape Retrieval in Shape Data Management. Computer 28(9), 57–62 (1995)
Pawlak, Z.: Rough Sets. Int. Journal on Inform. Comput. Sci. 11(5), 341–356 (1982)
Swain, M.J., Ballard, D.H.: Color Indexing. Int J. Computer Vision 7(1), 11–32 (1991)
Petrosino, A.: Rough fuzzy sets and unsupervised neural learning: applications in computer vision. In: Bonarini, A., Mancini, D., Masulli, F., Petrosino, A. (eds.) New trends in Fuzzy Logic, pp. 166–176. World Scientific, Singapore (1996)
Santini, S., Jain, R.: Similarity Measures. IEEE Trans. Pattern Analysis and Machine Intelligence 21(9), 871–883 (1999)
Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-Based Image Retrieval at the End of the Early Years. IEEE Trans. Pattern Analysis and Machine Intelligence 22(12), 1349–1380 (2000)
Stricker, M., Orengo, M.: Similarity of Color Images. In: Niblack, W.R., Jain, R.C. (eds.) Proc. SPIE Conf. on Storage and Retrieval for Image and Video Databases III, pp. 381–392 (1995)
Zhu, S.C., Yuille, A.L.: Unifying Snake/balloon, Region Growing and Bayes/MDL/Energy for multi-band Image Segmentation. IEEE Trans. Pattern Analysis and Machine Intelligence 18(9), 884–900 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ceccarelli, M., Musacchia, F., Petrosino, A. (2005). A Fuzzy Scale-Space Approach to Feature-Based Image Representation and Retrieval. In: De Gregorio, M., Di Maio, V., Frucci, M., Musio, C. (eds) Brain, Vision, and Artificial Intelligence. BVAI 2005. Lecture Notes in Computer Science, vol 3704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11565123_36
Download citation
DOI: https://doi.org/10.1007/11565123_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29282-1
Online ISBN: 978-3-540-32029-6
eBook Packages: Computer ScienceComputer Science (R0)