Universiti Teknologi Malaysia Institutional Repository

Gradual color clustering elimination for outdoor image segmentation

Abbasi, Hossein and Mohd Daud, Salwani and Amir Sjarif, Nilam Nur and Abbasi, Morteza and Adam, Mohamad Zulkefli and Yuhaniz, Siti Sophiayati (2016) Gradual color clustering elimination for outdoor image segmentation. Opoijien International Journal of Informatics Oiji, 4 (1). pp. 25-31. ISSN 2289-2370

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Abstract

One of the color reduction methods is color clustering, which has been applied for segmentation. Nonetheless, it has not been an appropriate method due to the automatically images change by luminance effects and color/texture variety. Hence, it can be done by improving the usual color clustering methods called customizing segmentation methods. This study focuses on customizing the color clustering methods for segmentation and object recognition in the outdoor images by utilizing a multi - phase procedure through a multi - resolution platform, based on self - organizing neural network, call ed gradual color Cluster Elimination (GCCE). The proposed method has been evaluated on outdoor images dataset namely BSDS and the results have been compared to PRI, NPR, and GCE statistical metrics of the latest segmentation methods which demonstrated that the proposed method has a satisfactory performance for the segmentation of the outdoor scenes.

Item Type:Article
Additional Information:RADIS System Ref No:PB/2016/09871
Subjects:T Technology
Divisions:Advanced Informatics School
ID Code:68227
Deposited By: Haliza Zainal
Deposited On:02 Nov 2017 02:55
Last Modified:14 Nov 2017 06:23

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