Texture segmentation using Gabor filter and multi-layer perceptron

Previous approaches to texture analysis and segmentation pe$orm multi-channel filtering by applying a set of filters in frequency domain or a set of masks in spatialdomain. In this paper we describe a texture segmentation algorithm based on multi-channel filtering in conjunction with neural networks for feature extraction and segmentation. The features extracted by Gabor filters have been applied for image segmentation and analysis. There are some important considerations about filter parameters and the reduction of feature dimensions. Here we introduce a method ta extract optimal feature dimensions using competitive networks and multilayer perceptrons. We present the segmentation results using different banhidths. The comparison of segmentation results generated using our method andprevious research wing leaming vector quantization (LVQ) is presented.