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Adaptive striping watershed segmentation method for processing microscopic images of overlapping irregular‐shaped and multicentre particles
Author(s) -
XIAO X.,
BAI B.,
XU N.,
WU K.
Publication year - 2015
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12207
Subject(s) - data striping , watershed , segmentation , computer science , artificial intelligence , particle (ecology) , pattern recognition (psychology) , computer vision , biology , ecology , operating system
Summary Oversegmentation is a major drawback of the morphological watershed algorithm. Here, we study and reveal that the oversegmentation is not only because of the irregular shapes of the particle images, which people are familiar with, but also because of some particles, such as ellipses, with more than one centre. A new parameter, the striping level , is introduced and the criterion for striping parameter is built to help find the right markers prior to segmentation. An adaptive striping watershed algorithm is established by applying a procedure, called the marker searching algorithm , to find the markers, which can effectively suppress the oversegmentation. The effectiveness of the proposed method is validated by analysing some typical particle images including the images of gold nanorod ensembles.