Red Blood Cells Detecting Depending on Binary Conversion at Multi Threshold Values
Keywords:Abnormal RBCs, binary image, RBCs detection, morphology, fill in the gaps
Automatic detection of Red Blood Cells (RBCs) by using image-processing techniques is important in determining blood disorders and diseases. This study proposes an algorithm for automatic detection of red blood cells in optical microscopy images of blood smears. The proposed method depends on binary conversion at multi-threshold and includes a morphological operation as erosion and image fill according to certain conditions. In this study, we used 50 images from IDB data of blood samples taken with an optical microscope. The suggested method is compared with other modern techniques based on the two accuracy coefficients, namely, detection and false alarm rates. Results show that the proposed method has a high detection accuracy compared to other methods.
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