Invariant moment based feature analysis for abnormal erythrocyte recognition

Erythrocyte shape recognition is very important in the detection of thalassemia and anemia using microscopic images. This study aims to develop a computer aided shape recognizer for the recognition of abnormal shapes viz., tear drop, echinocyte, eliptocyte. Here such recognition is done using Hu's moments and other geometric features followed by gray level thresholding and marker controlled watershed segmentation. These features are statistically evaluated to show their significant in discriminating the mentioned abnormal and normal shapes. In the result, it is found that six moment based features are significant.