Thresholding based on variance and intensity contrast

Authors:
Yu Qiao;Qingmao Hu;Guoyu Qian;Suhuai Luo;Wieslaw L. Nowinski
Affiliations:
Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore;Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore;Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore;School of Design, Communication and Information Technology, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia;Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
Venue:
Pattern Recognition
Year:
2007

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Abstract

A new thresholding criterion is formulated for segmenting small objects by exploring the knowledge about intensity contrast. It is the weighted sum of within-class variance and intensity contrast between the object and background. Theoretical bounds of the weight are given for the uniformly distributed background and object, followed by the procedure to estimate the weight from prior knowledge. Tests against two real and two synthetic images show that small objects can be extracted successfully irrespective of the complexity of background and difference in class sizes.