Supervised grayscale thresholding based on transition regions

Title: Supervised grayscale thresholding based on transition regions
Creator: Hu, Qingmao; Luo, Suhuai; Qiao, Yu; Qian, Guoyu
Relation: Image and Vision Computing Vol. 26, Issue 12, p. 1677-1684
Publisher Link: http://dx.doi.org/10.1016/j.imavis.2008.05.003
Publisher: Elsevier
Resource Type: journal article
Date: 2008
Description: A new thresholding framework is proposed which is transition region based, and consists of deriving the transition region with the help of supervision and calculating the threshold from the transition region. Four ways of supervision are studied: picking up an object and a background pixel, from other clustering or segmentation results, based on sample statistics, and exploration of background proportions. The approach has been validated both quantitatively and qualitatively. It is found that the proposed approach: (1) is more robust, consistent and reliable than the conventional transition-region-based thresholding methods; and (2) is easier to implement and has wider applicability than existing supervised thresholding methods. The approach is especially useful for segmenting difficult images with multiple objects and/or serious imaging artifacts.
Subject: grayscale thresholding; transition region; supervision; prior knowledge
Identifier: uon:5624
Identifier: http://hdl.handle.net/1959.13/43524
Identifier: ISSN:0262-8856
Reviewed

		Thumbnail	File	Description	Size	Format