Segmentation of electron microscopy images through Gabor texture descriptors

Rafael Fonolla Navarro; Oscar Nestares

doi:10.1117/12.234747

13 March 1996 Segmentation of electron microscopy images through Gabor texture descriptors

Rafael Fonolla Navarro, Oscar Nestares

Author Affiliations +

Proceedings Volume 2666, Image and Video Processing IV; (1996) https://doi.org/10.1117/12.234747
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

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.

Citation Download Citation

Rafael Fonolla Navarro and Oscar Nestares "Segmentation of electron microscopy images through Gabor texture descriptors", Proc. SPIE 2666, Image and Video Processing IV, (13 March 1996); https://doi.org/10.1117/12.234747

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