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Combined nearest mean classifiers for multiple feature classification

Abdullah, , and Ku-Mahamud, Ku Ruhana (2011) Combined nearest mean classifiers for multiple feature classification. In: 3rd International Conference on Computing and Informatics (ICOCI 2011), 8-9 June 2011 , Bandung, Indonesia.

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Pattern classification is an important stage in many image processing applications. This paper proposes a technique that is based on nearest mean classifier for classification.The proposed technique integrates three classifiers and uses colour and shape features. Experiment on small training samples has been conducted to evaluate the performance of the proposed combined nearest mean classiffiers and results obtained showed that the technique was able to provide good accuracy

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN 978-983-2078-49-4 Organized by: UUM College of Arts and Sciences, Universiti Utara Malaysia.
Uncontrolled Keywords: classification, multiple classifier combination, nearest mean classifier, multiple features
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: College of Arts and Sciences
Depositing User: Prof. Dr. Ku Ruhana Ku Mahamud
Date Deposited: 21 Dec 2011 03:59
Last Modified: 07 Apr 2015 03:26
URI: http://repo.uum.edu.my/id/eprint/3999

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