A Novel Method for Splitting Clumps of Convex Objects Incorporating Image Intensity and Using Rectangular Window-Based Concavity Point-Pair Search
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A Novel Method for Splitting Clumps of Convex Objects Incorporating Image Intensity and Using Rectangular Window-Based Concavity Point-Pair Search. / Farhan, Muham; Yli-Harja, Olli; Niemistö, Antti.
In: Pattern Recognition, Vol. 46, No. 3, 2013, p. 741-751.Research output: Contribution to journal › Article › Scientific › peer-review
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TY - JOUR
T1 - A Novel Method for Splitting Clumps of Convex Objects Incorporating Image Intensity and Using Rectangular Window-Based Concavity Point-Pair Search
AU - Farhan, Muham
AU - Yli-Harja, Olli
AU - Niemistö, Antti
N1 - Contribution: organisation=sgn,FACT1=1<br/>Portfolio EDEND: 2013-02-27<br/>Publisher name: Pergamon
PY - 2013
Y1 - 2013
N2 - A novel nonparametric concavity point analysis-based method for splitting clumps of convex objects in binary images is presented. The method is based on finding concavity point-pairs by using a variable-size rectangular window. The concavity point-pairs can be either connected with a straight split line or with a line that follows a path of minimum or maximum intensity on an accompanying grayscale image. Using straight lines can result in non-smooth contours. Therefore, post-processing steps that remove acute angles between split lines are proposed. Results obtained with images that have clumps of biological cells show that the method gives accurate results.
AB - A novel nonparametric concavity point analysis-based method for splitting clumps of convex objects in binary images is presented. The method is based on finding concavity point-pairs by using a variable-size rectangular window. The concavity point-pairs can be either connected with a straight split line or with a line that follows a path of minimum or maximum intensity on an accompanying grayscale image. Using straight lines can result in non-smooth contours. Therefore, post-processing steps that remove acute angles between split lines are proposed. Results obtained with images that have clumps of biological cells show that the method gives accurate results.
U2 - 10.1016/j.patcog.2012.09.008
DO - 10.1016/j.patcog.2012.09.008
M3 - Article
VL - 46
SP - 741
EP - 751
JO - Pattern Recognition
JF - Pattern Recognition
SN - 0031-3203
IS - 3
ER -