This paper proposes a novel system for color image segmentation called “Adaptive color image segmentation using fuzzy min-max clustering (ACISFMC)”. The present work is an application of Simpson’s fuzzy min-max neural network (FMMN) clustering algorithm. ACISFMC uses a multilayer perceptron (MLP) like network which perform color image segmentation using multilevel thresholding. Threshold values...

Color Image quantization (CQ) is an important problem in computer graphics, image and processing. The aim of quantization is to reduce colors in an image with minimum distortion. Clustering is a widely used technique for color quantization; all colors in an image are grouped to small clusters. In this paper, we proposed a new hybrid approach for color quantization using firefly algorithm (FA) a...

Color quantization is wildly applied especially in the fields of computer graphics and image processing. After studying the solutions of color clustering, a new approach based on ant colony clustering algorithm applied in color image quantization is proposed in the paper. According to the picking up— dropping theory, a promoted ant algorithm is applied to group colors into certain clusters in R...

Colors in an image provides tremendous amount of information. Using this color information images can be segmented, analyzed, labeled and indexed. In content based image retrieval system, color is one of the basic primitive features used. In Prevalent Color Extraction and indexing, the most extensive color on an image is identified and it is used for indexing. For implementation, Asteroideae fl...

Availability of Huge image datasets and requirement of employing them causes necessity of effective methods for managing them. Extracting efficient features from images is one of the most important requirements in managing techniques such as image retrieval, indexing, classification, clustering and etc. Identifying the descriptive and discriminatory features is valuable and essential. In this p...

This paper develops a computationally efficient process for segmentation of color images. The input image is partitioned into a set of output images in accordance to color characteristics of various image regions. The algorithm is based on random sampling of the input image and fuzzy clustering of the training data followed by crisp classification of the input image. The user prescribes the num...

We extend the mass-halo formalism for analytically generating power spectra to allow for the different clustering behavior observed in galaxy sub-populations. Although applicable to other separations, we concentrate our methods on a simple separation by rest-frame color into “red” and “blue” sub-populations through modifications to the 〈N〉(M) relations and halo distribution functions for each o...