Open AccessWhite Blood Cell Detection Depending on Binary Analysis Based on Red, Blue and Hue Components
Author(s) -
Mohammed H. Mohammed,
Hazim G. Daway,
Jamela Jouda
Publication year - 2020
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.55.1.45
Subject(s) - hue , artificial intelligence , white (mutation) , red blood cell , computer science , binary number , pattern recognition (psychology) , computer vision , binary image , filter (signal processing) , image processing , image (mathematics) , mathematics , medicine , chemistry , biochemistry , arithmetic , gene
The automatic detection of white blood cells remains an unresolved problem in medical imaging. white blood cell image analysis has included researchers from the fields of medicine and computer vision alike. In this paper, a new algorithm for white blood cell detection is proposed. This algorithm is based on the binary conversion of red and blue identity compounds and gradient after defining the values of specific areas while deleting unwanted small areas depending on the median filter. In the experimental results from white blood cell images, the proposed algorithm was compared with several other algorithms for detection. A quality scale was used that compares manual cell counts with the automatic detection of algorithms where the proposed algorithm obtained a high distinction accuracy reaching 98 percent, as compared to other methods.