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Sewage pipe image segmentation using a neural based architecture
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DOI：10.1016/0167-8655(95)00132-8.png)
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Abstract
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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 colinear and noncollinear receptive fields at the Cooperation Stage; and the pre-processing of the input signal using a Spatial Complex Logarithmic Mapping.
Keywords:
boundary contour system
Gabor filters
spatial complex logarithmic mapping
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