Paper Title
A Red Blood Cell Recognition System of Anemia based on Blood Smear Images

In blood testing, evaluating whether a person has anemia usually uses hematology analyzer to analysis some factors, such as Hemoglobin (Hb), Red blood cell (RBC), mean corpuscular volume (MCV), etc. However, hematology analyzer is very expensive for general clinics. In order to solve this problem, this thesis proposes a new estimation method based on 2-dimensions blood smear images to develop a mechanism that can help doctors to do diagnosis.The proposed method judges whether the red blood cells belong to one of five anemia blood classes according to the shape of single RBC in blood smear images. These five classes are Acanthocytes, Schistocytes, Circle, Oval, and Teardrop. Index Terms - Segmentation, RBC, Morphology, Genetic algorithm.