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Segmentation of Images through Clustering to Extract Color Features: An Application forImage Retrieval

Main Authors: M. V. Sudhamani, C. R. Venugopal
Format: Article eJournal
Bahasa: eng
Terbitan: , 2007
Subjects:
Segmentation
Clustering
Image Retrieval
Features
Online Access: https://zenodo.org/record/1061042
ctrlnum 1061042
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language eng
format Journal:Article
Journal
Journal:eJournal
author M. V. Sudhamani
C. R. Venugopal
title Segmentation of Images through Clustering to Extract Color Features: An Application forImage Retrieval
publishDate 2007
topic Segmentation
Clustering
Image Retrieval
Features
url https://zenodo.org/record/1061042
contents This paper deals with the application for contentbased image retrieval to extract color feature from natural images stored in the image database by segmenting the image through clustering. We employ a class of nonparametric techniques in which the data points are regarded as samples from an unknown probability density. Explicit computation of the density is avoided by using the mean shift procedure, a robust clustering technique, which does not require prior knowledge of the number of clusters, and does not constrain the shape of the clusters. A non-parametric technique for the recovery of significant image features is presented and segmentation module is developed using the mean shift algorithm to segment each image. In these algorithms, the only user set parameter is the resolution of the analysis and either gray level or color images are accepted as inputs. Extensive experimental results illustrate excellent performance.
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institution Universitas PGRI Palembang
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