Texture Edge Detection using Multi-resolution Features and SOM

Texture boundaries or edges are useful information for segmenting a texture image. We propose a texture edge detection algorithm using a bank of 1-D multi-channel, multiresolution filters and self organizing map (SOM). 2-D filtering smears the effect of an edge in all directions, and hence we used 1-D filtering that will only smear the edge in the direction of filtering. SOM reduces the dimension of a feature vector by producing a 1-D map which plots the similarities of data by grouping similar items together. The output of SOM is processed to obtain the texture edge map. The proposed methodology is tested on simulated as well as natural texture images and produces satisfactory results.