Sewage pipe image segmentation using a neural based architecture

Koppen, M

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 colinear and noncollinear receptive fields at the Cooperation Stage; and the pre-processing of the input signal using a Spatial Complex Logarithmic Mapping.

Más información

Título según WOS: ID WOS:A1996UG65600006 Not found in local WOS DB
Título de la Revista: PATTERN RECOGNITION LETTERS
Volumen: 17
Número: 4
Editorial: ELSEVIER SCIENCE BV
Fecha de publicación: 1996
Página de inicio: 363
Página final: 368
Notas: ISI