Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/43756
標題: AN ADAPTABLE THRESHOLD DECISION METHOD
作者: Tsai, M.H.
蔡孟勳
Wang, M.H.
Chang, T.Y.
Pai, P.Y.
Chan, Y.K.
Chen, J.M.
詹永寬
關鍵字: Thresholding
Otsu's method
Image segmentation
Serial images
particle swarm optimization
segmentation
performance
images
cancer
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.
URI: http://hdl.handle.net/11455/43756
ISSN: 1349-4198
Appears in Collections:資訊管理學系

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