文章基本信息

标题：Particle Swarm Optimization for Nano-Particles Extraction from Supporting Materials
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作者：Dr. Mohamed abdElRahman Abdou
期刊名称：International Journal of Image Processing (IJIP)
电子版ISSN：1985-2304
出版年度：2011
卷号：5
期号：3
页码：361-370
出版社：Computer Science Journals
摘要：Metallic and non-metallic nano-particles have attracted much interest concerning their wide applications. Transmission electron microscopy (TEM) is the state of the art method to characterize a nano-particle with respect to size, morphology, structure, or composition. This paper presents an efficient evolutionary computational method, particle swarm optimization (PSO), for automatic segmentation of nano-particles. A threshold-based segmentation technique is applied, where image entropy is attacked as a minimization problem to specify local and global thresholds. We are concerned with reducing wrong characterization of nano-particles due to concentration of liquid solutions or supporting material within the acquired image. The obtained results are compared with manual techniques and with previous researches in this area.
关键词：TEM Image Scaning; Particle Swarm Optimization; Image Segmentation; Nano-particles Characterization