Abstract
Image segmentation techniques are very useful in the analysis of aerial images, biomedical images and seismic images as well as in the automation of industrial applications. The paper presents a few texture-specific features for the segmentation of texture images. We will present four approaches to texture segmentation, viz, descriptor based, heuristic function based, defuzzified feature based and Mask feature based. We have mainly used FCM for texture segmentation.
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Chaudhuri, B.B., Sarkar, N.: Texture Segmentation Using Fractal Dimension. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(1) (1995)
Hanmandlu, M., Madasu, V.K., Vasikalra, S.: A Fuzzy Approach to Texture Segmentation. In: Proceeding of ITCC 2004: Coding and Computing (2004)
Laws, K.I.: Texture Energy Measures. In: DARPA Image Understanding Workshop, DARPA, Los Altos, CA, pp. 47–51 (1979)
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© 2005 Springer-Verlag Berlin Heidelberg
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Hanmandlu, M., Agarwal, S., Das, A. (2005). A Comparative Study of Different Texture Segmentation Techniques. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2005. Lecture Notes in Computer Science, vol 3776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590316_74
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DOI: https://doi.org/10.1007/11590316_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30506-4
Online ISBN: 978-3-540-32420-1
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