Color-based image segmentation classifies pixels of digital images in numerous groups for
further analysis in computer vision, pattern recognition, image understanding, and image …

Image segmentation is vital for meaningful analysis and interpretation of the medical
images. The most popular method for clustering is k-means clustering. This article presents …

This paper reviews the method of classification of the types of images used in data
concealment based on the perspective of the researcher's efforts in the past decade …

Multiobjective optimization methods in image analysis are one of the active research
domains in the current years. These methods are used for the decision-making process in …

List of References on Evolutionary Multiobjective Optimization Page 1 List of References on
Evolutionary Multiobjective Optimization Carlos A. Coello Coello ccoello@cs.cinvestav.mx …

Image enhancement and segmentation are the two imperative steps while processing digital
images. The goal of enhancement is to improve the quality of images so as to nullify the …

This paper provides a brief introduction to the so-called multi-objective evolutionary
algorithms, which are bio-inspired metaheuristics designed to deal with problems having …

A novel image segmentation algorithm based on the adaptive edge detection and an
improved mean shift is proposed. According to the Ostu method, an adaptive threshold …

Segmentation is targeted to partition an image into distinct regions comprising pixels having
similar attributes. In the context of image analysis and interpretation, these partitioned …

Image segmentation fusion is defined as the set of methods which aim at merging several
image segmentations, in a manner that takes full advantage of the complementarity of each …