title: Automated leukocyte recognition using fuzzy divergence.
abstract: This paper aims at introducing an automated approach to leukocyte recognition using fuzzy divergence and modified thresholding techniques. The recognition is done through the segmentation of nuclei where Gamma, Gaussian and Cauchy type of fuzzy membership functions are studied for the image pixels. It is in fact found that Cauchy leads better segmentation as compared to others. In addition, image thresholding is modified for better recognition. Results are studied and discussed.
authors.affiliation: School of Medical Science and Technology, I.I.T., Kharagpur, West Bengal, India.
authors.forename: Madhumala
authors.initials: M
authors.lastname: Ghosh
authors.forename: Devkumar
authors.initials: D
authors.lastname: Das
authors.forename: Chandan
authors.initials: C
authors.lastname: Chakraborty
authors.forename: Ajoy K
authors.initials: AK
authors.lastname: Ray
mesh_terms: D002467:Cell Nucleus / Q000648:ultrastructure; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007962:Leukocytes / Q000166:cytology*; D008853:Microscopy / Q000379:methods*