Open AccessRed blood cells and white blood cells detection by image processing
Author(s) -
Irwan Rahadi,
Meechoke Choodoung,
Arunsri Choodoung
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1539/1/012025
Subject(s) - adaboost , boosting (machine learning) , artificial intelligence , computer science , technician , blood smear , pattern recognition (psychology) , identification (biology) , computer vision , medicine , pathology , support vector machine , biology , engineering , botany , malaria , electrical engineering
The common method of red and white blood cells identification and counting consider the manual processes on microscope which is arranged by the laboratory’s technician with their own experience. In this research, we will develop a computer program to detect and identify the proposed objects based on their pattern. The proposed objects are Red Blood Cells (RBCs), and White Blood Cells (WBCs). For blood cells identification and classification, an idea of Viola and Jones will be followed. Adaboost (adaptive boosting) method will be applied to increase the accuracy of the error of learning algorithm. The output of the proposed program shows that all the types of cells mentioned can be detected and classify effectively by showing the number and time spent of cells detected.