Image Segmentation Using an Improved Hybrid Modelling

An Improved Pixon-Based Approach for Image Segmentation

An improved pixon-based method is proposed in this paper for image segmentation. In thisapproach, a wavelet thresholding technique is initially applied on the image to reduce noise and toslightly smooth the image. This technique causes an image not to be oversegmented when the pixonbasedmethod is used. Indeed, the wavelet thresholding, as a pre-processing step, eliminates theunnecessary details...

Hybrid Image Segmentation Using Watersheds

Image Segmentation using Improved Imperialist Competitive Algorithm and a Simple Post-processing

Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentati...

Unsupervised Texture Image Segmentation Using MRFEM Framework

Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...

An Improved Medical Image Segmentation Using Charged Fluid Model

Segmentation has a major role to play in the field of medical imaging for effectively detecting the deformities. Though there are huge medical imaging techniques available, Magnetic Resonance Image (MRI) is widely used because of the non-ionizing radiation which is being used. In this paper, we proposed a refined method using charged fluid model (CFM) which yields better results. It is essentia...