Using Watershed Algorithm in Independent Component Image Analysis

Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/6240

Title:	Using Watershed Algorithm in Independent Component Image Analysis
Authors:	游正義
Contributors:	資訊工程系
Date:	2013-06
Issue Date:	2017-10-02 09:26:11 (UTC+8)
Abstract:	As the image quality and computer computing power develop, the un- modifiable physical storage mode of images has turned into modifiable digital storage. However, although the present digital preservation technology of images develops increasingly, there are still many unpredictable variables influencing the preservation quality of a digital image. The quality usually depends on the usage mode of the user or the variables resulted from natural environment. Therefore, if the brightness distribution of an image after image analysis is too extreme, the formed subject matter will be difficult to be recognized. This study combined Independent Component Analysis (ICA) with watershed algorithm, and carried out principal component analysis for the R, G and B color planes of the imported color digital images, in order to achieve better effect on the detection and tracking of primary target than the previously proposed ICA. Experiment results indicate that our approach has great improvement on the images information interpreted and recognized. © 2013 ISSN 2185-2766. (12 refs)
Relation:	ICIC Express Letters, Part B: Applications
Appears in Collections:	[Department of Computer Science and Information Engineering] 【資訊工程系所】期刊論文

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