DefinePK

Abstract

Red blood cell (RBC) diagnosis is very important process for early detection of blood related disease such as malaria and anemia before suitable follow up treatment can be proceed. Conventional method is conducted by pathologist by manually count and classifies the viewed cell under light microscope. Such process is tedious and required highly skill and experience pathologist to analyze the shape of the red blood cell and consequently counting its number. In this paper an automated RBC counting and classification system is proposed by using National Instrument (NI) Vision Builder Automated Inspection (AI) tool to speed up the time consumption to analyze the RBC and to reduce the potential of the wrongly identified RBC. Initially the RBC image undergoes image pre-processing steps which involved global threshold of method applied green channel color image. Then it continues with RBC counting by using particle area and calculator numeric function method. Eventually, Heywood Circularity Factor method is applied for normal and abnormal RBC classification. The proposed method has been tested on blood cell images and the effectiveness and reliability of the system has been demonstrated.