Image Segmentation of Cows using Thresholding and K-Means Method

Image Segmentation Using Semi-Supervised k-Means

Extracting the region of interest is a very challenging task in Image Processing. Image segmentation is an important technique for image processing which aims at partitioning the image into different homogeneous regions or clusters. Lots of general-purpose techniques and algorithms have been developed and widely applied in various application areas. In this paper, a Semi-Supervised k-means segm...

Segmentation of Photospheric Solar Images by Using c-Means,k-Means, and FCM Algorithms

Image Edge Detection and Segmentation by using Histogram Thresholding method

A new approach used for image edge deduction, segmentation and normalization illumination under varying lighting conditions are presented. Edge detection refers to the process of identifying and locating sharp by applying smooth and noisy clinical technic in an image. It has favorable applications in the fields such as machine vision, pattern recognition, object recognition, motion analysis, pa...

Non linear Image segmentation using fuzzy c means clustering method with thresholding for underwater images

The quality of underwater images is directly affected by water medium, atmosphere, pressure and temperature. This emphasizes the necessity of image segmentation, which divides an image into parts that have strong correlations with objects to reflect the actual information collected from the real world. Image segmentation is the most practical approach among virtually all automated image recogni...

Image Segmentation With Modified K-Means Clustering Method

Image segmentation is used to recognizing some objects or something that is more meaningful and easier to analyze In this paper we are focus on the the K means clustering for segmentation of the image. K-means clustering is the most widely used clustering algorithm to position the radial basis function (RBF) centres. Its simplicity and ability to perform on-line clustering may inspire this choi...