Remove Unimportant Features from True Colored Images Using the Segmentation Technique

In this work a new approach was built to apply k-means algorithm on true colored images (24bit images) which are usually treated by researchers as three image (RGB) that are classified to 15 class maximum only. We find the true image as 24 bit and classify it to more than 50 classes. As we know k-me...

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Main Author: Shahad Hasso
Format: Article
Language:English
Published: Mosul University 2010-12-01
Series:Al-Rafidain Journal of Computer Sciences and Mathematics
Subjects:
Online Access:https://csmj.mosuljournals.com/article_163932_27de4e36c34259d5baba8eafbc2d33ed.pdf
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author Shahad Hasso
author_facet Shahad Hasso
author_sort Shahad Hasso
collection DOAJ
description In this work a new approach was built to apply k-means algorithm on true colored images (24bit images) which are usually treated by researchers as three image (RGB) that are classified to 15 class maximum only. We find the true image as 24 bit and classify it to more than 50 classes. As we know k-means algorithm classify images to many independent classes or features and we could increase the class number therefore we could remove the classes or features that have minimum number of pixels which are considered unimportant features and reconstruct the images. Correlation factor and Signal to Noise Ratio were used to measure the work and the results seems that by increasing the image resolution the effect of removing minimum features is decreased. The CSharp (Visual Studio 2008) programming language was used to build the algorithms which are able to allocate huge matrices in high execution time.
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publishDate 2010-12-01
publisher Mosul University
record_format Article
series Al-Rafidain Journal of Computer Sciences and Mathematics
spelling doaj-art-1327405b7faf41a6a403fecab970dc502025-08-20T03:17:02ZengMosul UniversityAl-Rafidain Journal of Computer Sciences and Mathematics1815-48162311-79902010-12-017312113410.33899/csmj.2010.163932163932Remove Unimportant Features from True Colored Images Using the Segmentation TechniqueShahad Hasso0College of Computing and Mathematics University of MosulIn this work a new approach was built to apply k-means algorithm on true colored images (24bit images) which are usually treated by researchers as three image (RGB) that are classified to 15 class maximum only. We find the true image as 24 bit and classify it to more than 50 classes. As we know k-means algorithm classify images to many independent classes or features and we could increase the class number therefore we could remove the classes or features that have minimum number of pixels which are considered unimportant features and reconstruct the images. Correlation factor and Signal to Noise Ratio were used to measure the work and the results seems that by increasing the image resolution the effect of removing minimum features is decreased. The CSharp (Visual Studio 2008) programming language was used to build the algorithms which are able to allocate huge matrices in high execution time.https://csmj.mosuljournals.com/article_163932_27de4e36c34259d5baba8eafbc2d33ed.pdftrue colored imagescorrelationsegmentation technique
spellingShingle Shahad Hasso
Remove Unimportant Features from True Colored Images Using the Segmentation Technique
Al-Rafidain Journal of Computer Sciences and Mathematics
true colored images
correlation
segmentation technique
title Remove Unimportant Features from True Colored Images Using the Segmentation Technique
title_full Remove Unimportant Features from True Colored Images Using the Segmentation Technique
title_fullStr Remove Unimportant Features from True Colored Images Using the Segmentation Technique
title_full_unstemmed Remove Unimportant Features from True Colored Images Using the Segmentation Technique
title_short Remove Unimportant Features from True Colored Images Using the Segmentation Technique
title_sort remove unimportant features from true colored images using the segmentation technique
topic true colored images
correlation
segmentation technique
url https://csmj.mosuljournals.com/article_163932_27de4e36c34259d5baba8eafbc2d33ed.pdf
work_keys_str_mv AT shahadhasso removeunimportantfeaturesfromtruecoloredimagesusingthesegmentationtechnique