Sewage pipe image segmentation using a neural based architecture
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 |
| Fecha de publicación: | 1996 |
| Página de inicio: | 363 |
| Página final: | 368 |
| Notas: | ISI |