Litcius/Paper detail

Red blood cells and white blood cells detection by image processing

Irwan Rahadi, Meechoke Choodoung, Arunsri Choodoung

2020Journal of Physics Conference Series17 citationsDOIOpen Access PDF

Abstract

Abstract 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.

Topics & Concepts

AdaBoostBoosting (machine learning)Artificial intelligenceComputer scienceTechnicianBlood smearPattern recognition (psychology)Identification (biology)Computer visionMedicinePathologySupport vector machineBiologyEngineeringMalariaBotanyElectrical engineeringDigital Imaging for Blood DiseasesImage Processing Techniques and ApplicationsImage and Object Detection Techniques
Red blood cells and white blood cells detection by image processing | Litcius