UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 11 | November 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 5 Issue 4
April-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIR1804468


Registration ID:
522801

Page Number

28-32

Share This Article


Jetir RMS

Title

Denoising-based Clustering Algorithms for -Corrupted Images

Authors

Abstract

Clustering algorithm is a widely used segmentation method in image processing applications. The algorithm can be easily implemented; however in the occurrence of noise during image acquisition, this might affect the processing results. In order to overcome this drawback, this paper presents a new clustering-based segmentation technique that may be able to find different applications in image segmentation. The proposed algorithm called Denoising-based (DB) clustering algorithm has three variations namely, Denoising-based-K-means (DB-KM), Denoising-based-Fuzzy C- means (DB-FCM), and Denoising-based-Moving K-means (DB- MKM). The proposed DB-clustering algorithms are able to minimize the effects of the Salt-and-Pepper noise during the segmentation process without degrading the fine details of the images. These methods incorporate a noise detection stage to the clustering algorithm, producing an adaptive segmentation technique specifically for segmenting the noisy images. The results obtained quantitatively and qualitatively have favored the proposed DB-clustering algorithms, which consistently outperform the conventional clustering algorithms in segmenting the noisy images. Thus, these DB-clustering algorithms could be possibly used as pre- or post-processing (i.e., segmenting images into regions of interest) in consumer electronic products such as television and monitor with their capability of reducing noise effect.

Key Words

clustering, image segmentation, salt- and- pepper noise, image processing.

Cite This Article

"Denoising-based Clustering Algorithms for -Corrupted Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 4, page no.28-32, April-2018, Available :http://www.jetir.org/papers/JETIR1804468.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Denoising-based Clustering Algorithms for -Corrupted Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 4, page no. pp28-32, April-2018, Available at : http://www.jetir.org/papers/JETIR1804468.pdf

Publication Details

Published Paper ID: JETIR1804468
Registration ID: 522801
Published In: Volume 5 | Issue 4 | Year April-2018
DOI (Digital Object Identifier):
Page No: 28-32
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

000135

Print This Page

Current Call For Paper

Jetir RMS