Cellular Learning Automata-Based Color Image Segmentation using Adaptive Chains
Publish place: 14th annual International CSI Computer Conference
Publish Year: 1388
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CSICC14_069
تاریخ نمایه سازی: 24 خرداد 1388
Abstract:
This paper presents a new segmentation method for color images. It relies on soft and hard segmentation processes. In the soft segmentation process, a cellular learning automata analyzes the input image and closes together the pixels that are enclosed in each region to generate a soft segmented image. Adjacency and texture information are encountered in the soft segmentation stage. Soft segmented image is then fed to the hard segmentation process to generate the final segmentation result. As the proposed method is based on CLA it can adapt to its environment after some iterations. This adaptive behavior leads to a semi content-based segmentation process that performs well even in presence of noise. Experimental results show the effectiveness of the proposed segmentation method
Authors
Ahmad Ali Abin
Sharif University of Technology, Tehran, Iran
Mehran Fotouhi
Sharif University of Technology, Tehran, Iran
Shohreh Kasaei
Sharif University of Technology, Tehran, Iran