Please use this identifier to cite or link to this item:
|標題:||AN ADAPTABLE THRESHOLD DECISION METHOD||作者:||Tsai, M.H.
|關鍵字:||Thresholding;Otsu's method;Image segmentation;Serial images;particle swarm optimization;segmentation;performance;images;cancer||Project:||International Journal of Innovative Computing Information and Control||期刊/報告no：:||International Journal of Innovative Computing Information and Control, Volume 6, Issue 5, Page(s) 2285-2299.||摘要:||
Otsu's thresholding method (OTM) is one of the most commonly used thresholding methods. Unfortunately, the threshold obtained by OTM is biased in favor of the class, whose standard deviation or quantity (number) of data is larger. Besides, one may adopt distinct thresholds in different applications for a same data set. Accordingly, this paper proposes an adaptable threshold decision method (ATDM) to provide the most appropriate thresholds for assorted applications. This paper also proposes a PSO (particle swarm optimization) based parameters detector (PBPD) to decide the fittest parameters which are used by ATDM. Image segmentation extracts the regions of interest from an image for follow-up analyses, and thresholding is one important technique for image segmentation. This paper will employ ATDM to detect the object contours in an image in order to investigate the performance of ATDM. The experiments show that ATDM can give impressive segmentation results.
|Appears in Collections:||資訊管理學系|
Show full item record
TAIR Related Article
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.