Research on the novel pattern clustering algorithm based on particle swarm optimized adaptive wavelet neural network model

Image segmentation is an integral part of critical image processing applications. Segmentation involves removal of a region of interest from the background. Recent researches in segmentation incorporate clustering algorithms for separation or removal of regions of interest. Prominent segmentation algorithms include K - means which segment the region from the background and further median filtering could be utilized to remove the unwanted regions in the segmented image. This research paper utilizes an adaptive wavelet neural network model with training or learning process optimized by the particle swarm optimization algorithm. The proposed algorithm has been tested and experimental results indicate a high precision of segmentation when compared with the conventional techniques.