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Proceedings Paper

Segmentation of electron microscopy images through Gabor texture descriptors
Author(s): Rafael Fonolla Navarro; Oscar Nestares
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Paper Abstract

We have developed a robust method for image segmentation based on a local multiscale texture description. We first apply a set of 4 by 4 complex Gabor filters, plus a low-pass residual (LPR), producing a log-polar sampling of the frequency domain. Contrary to other analysis methods, our Gabor scheme produces a visually complete multipurpose representation of the image, so that it can also be applied to coding, synthesis, etc. Our sixteen texture features consist of local contrast descriptors, obtained by dividing the modulus of the response of the complex Gabor filter by that of the LPR at each location. Contrast descriptors are basically independent of slow variations in intensity, while increasing the robustness and invariance of the representation. Before applying the segmentation algorithm, we equalize the number of samples of the four layers in the resulting pyramid of local contrast descriptors. This method has been applied to segmentation of electron microscopy images, obtaining very good results in this real case, where robustness is a basic requirement, because intensity, textures and other factors are not completely homogeneous.

Paper Details

Date Published: 13 March 1996
PDF: 9 pages
Proc. SPIE 2666, Image and Video Processing IV, (13 March 1996); doi: 10.1117/12.234747
Show Author Affiliations
Rafael Fonolla Navarro, Consejo Superior de Investigaciones Cientificas (Spain)
Oscar Nestares, Consejo Superior de Investigaciones Cientificas (Spain)


Published in SPIE Proceedings Vol. 2666:
Image and Video Processing IV
Robert L. Stevenson; M. Ibrahim Sezan, Editor(s)

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