Segmentation of dental radiographs using a swarm intelligence approach

被引：0

作者：

Keshtkar, Fazel ^{[1
]}

Gueaieb, Wail ^{[1
]}

机构：

[1] Univ Ottawa, Sch Informat Technol & Engn, Ottawa, ON, Canada

来源：

2006 CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1-5 | 2006年

关键词：

swarm intelligence; image segmentation; cellular automata; knowledge-based reasoning;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

One of the most complex tasks in digital image processing is image segmentation. This paper proposes a novel image segmentation algorithm that uses a biologically inspired technique based on swarm intelligence and a cellular automata model. The proposed swarm intelligence-based algorithm operates on the image pixel data and a region/neighborhood map to form a context in which they can merge. The swarm intelligent algorithm also tries to find similar pixels using a sensor function, which is then utilized by swarm agents to determine the next appreciate pixel in the region/segment area. In addition, the paper introduces a cellular automata-based dynamic flow algorithm to guide swarm agents to choose the best possible advancing direction to avoid traffic jam and inconsistency. The suggested image segmentation strategy is tested on a set of dental radiographs.

引用

页码：611 / +

页数：2

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