mk:prl96

Summary

Sewage Pipe Image Segmentation using a Neural Based Architecture. Javier Ruiz-del-Solar and Mario Köppen. Pattern Recognition Letters, 17(4):363-368, 1996.

Abstract

This article describes a neural architecture for real-time segmentation of sewage pipe video images, which is based on processing mechanisms of the mammalian visual system and corresponds to a modified version of the Boundary Contour System. Remarkable aspects of the proposed architecture are: the use of odd-symmetric 2-D Gabor filters as receptive fields of the neurons at the Oriented Filtering Stage; the use of neurons with collinear and noncollinear receptive fields at the Cooperation Stage; and the pre-processing of the input signal using a Spatial Complex Logarithmic Mapping.

Bibtex entry

@ARTICLE { mk:prl96,
    ABSTRACT = { This article describes a neural architecture for real-time segmentation of sewage pipe video images, which is based on processing mechanisms of the mammalian visual system and corresponds to a modified version of the Boundary Contour System. Remarkable aspects of the proposed architecture are: the use of odd-symmetric 2-D Gabor filters as receptive fields of the neurons at the Oriented Filtering Stage; the use of neurons with collinear and noncollinear receptive fields at the Cooperation Stage; and the pre-processing of the input signal using a Spatial Complex Logarithmic Mapping. },
    AUTHOR = { Javier Ruiz-del-Solar and Mario Köppen },
    MODIFIED = { 2008-02-28 17:05:45 +0900 },
    HASABSTRACT = { Yes },
    JOURNAL = { Pattern Recognition Letters },
    NUMBER = { 4 },
    PAGES = { 363--368 },
    TITLE = { Sewage Pipe Image Segmentation using a Neural Based Architecture },
    VOLUME = { 17 },
    YEAR = { 1996 },
}