Advanced classifiers for red blood cell detection: A comprehensive survey

Recently many researchers concentrate on Blood cell segmentation and identification in pattern recognition. The blood cells play a crucial role in assessing health, as blood serves as a key indicator of well-being. The study highlights the impact of normocytic and microcytic red blood cell (RBC) analysis in clinical applications, particularly in diagnosing conditions like leukemia, anemia, and infections. This review paper investigated various techniques for detecting and classifying red blood cells based on their morphological characteristics and image processing algorithms. The red blood cells image samples were used for feature extraction techniques which involve thresholding, edge detection, and morphological operations etc. Pattern recognition system which involves stages like image acquisition, preprocessing, enhancement, segmentation, feature extraction, and algorithm implementation.