Classification of red blood cells disease using fuzzy logic theory

Blood cell classification is the initial process for detecting diseases; the diseases can be carried if it is detected at early stage. For solving such problems. Quantitative processing of digital images based on fuzzy technique is applied for classification of red blood cells. There are various features consist of shape, size and colour based features that based on statistical analysis (i.e. Mean, Standard Deviation, Variance, Roundness, Skewness, Kurtosis) have been extracted. The classification results indicated that these features highly signification and can be used for classification of red cells to the normal and up normal cells. The obtained result successfully identified 98% of red blood cells.