Gradual Color Clustering Elimination as a Novel and Efficient method for Outdoor Image Segmentation
Hossein Abbasi, Salwani Mohd, Nilam Nur Amir Sjarif, Morteza Abbasi, Mohamad Zulkefli Adam, Siti Sophiayati Yuhaniz · Open International Journal of Informatics · 2016
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 byluminance effects and color/texture variety. Hence, it can be done by improving the usual colorclustering methods called customizing segmentation methods. This study focuses on customizing thecolor clustering methods for segmentation and object recognition in the outdoor images by utilizing amulti-phase procedure through a multi-resolution platform, based on self-organizing neural network,called gradual color Cluster Elimination (GCCE). The proposed method has been evaluated onoutdoor images dataset namely BSDS and the results have been compared to PRI, NPR, and GCEstatistical metrics of the latest segmentation methods which demonstrated that the proposed methodhas a satisfactory performance for the segmentation of the outdoor scenes.