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dc.contributor.authorN. H., Harun
dc.contributor.authorMohd Yusoff, Mashor, Prof. Dr.
dc.contributor.authorH., Rosline
dc.date.accessioned2011-09-30T14:36:47Z
dc.date.available2011-09-30T14:36:47Z
dc.date.issued2011-06-20
dc.identifier.citationIFMBE Proceedings, vol. 35 (15), 2011, pages 617-622en_US
dc.identifier.isbn978-3-6422-1728-9
dc.identifier.issn1680-0737
dc.identifier.urihttp://www.springerlink.com/content/tm70n7r405t8020p/fulltext.pdf
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/13973
dc.descriptionLink to publisher's homepage at http://www.springerlink.comen_US
dc.description.abstractImage segmentation is an essential step in image analysis and is a requirement for feature extraction. One of the common segmentation techniques is using clustering algorithms. Currently, clustering algorithm has been used widely and popular in many fields such as in pattern recognition, image processing, and signal processing. These methods partition or group the objects of an image based on similarities and differences. This study proposed an automated color image segmentation technique using combination of saturation component base on HSI color space and clustering technique which are Moving K-means and Fuzzy K-means. Then, 7x7 pixels median filter was applied to remove unwanted noise after the segmentation process was completed. The comparison performance of the proposed technique was investigated. The experimental results yield a promising result for the combination of saturation component with Moving K-means clustering algorithm and 7x7 pixels median filter.en_US
dc.language.isoenen_US
dc.publisherSpringer-Verlagen_US
dc.relation.ispartofseriesProceedings of the 5th Kuala Lumpur International Conference on Biomedical Engineering (BIOMED 2011)en_US
dc.subjectAcute leukemia blood imagesen_US
dc.subjectClusteringen_US
dc.subjectFuzzy K-meansen_US
dc.subjectMoving K-meansen_US
dc.subjectSaturation componenten_US
dc.titleCluster approach for auto segmentation of blast in acute leukimia blood slide imagesen_US
dc.typeWorking Paperen_US


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