The aim of this paper is to study and identify various threshold values for two prevalently used edge detection techniques, which are Sobel and Canny. The purpose is to determine which value gives an accurate result for identifying a leukemic cell. Moreover, evaluating suitability of edge detectors is also essential as feature extraction of cell depends greatly on image segmentation (edge detection). Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML) is selected due to its diagnosing which were found lacking. Next, apply noise filters for the best of image quality. Thus by comparing image with no filter, median and average filters, useful information can be acquired. Each edge detectors is fixed with threshold value of 0-0.5 but for Cann edge detection the value can increase until 0.9. From the research, it is found that Canny edge with no filter and a threshold value of 0.7 gives a clearer image with less noise reduction.
