Comparison of edge detection techniques for M7 subtype Leukemic cell in terms of noise filters and threshold value
School of Microelectronic Engineering, University Malaysia Perlis, Pauh Putra Campus, 02600, Arau, Perlis, Malaysia
2 School of Computer and Communication Engineering, University Malaysia Perlis, Pauh Putra Campus, 02600, Arau, Perlis, Malaysia
* Corresponding author: firstname.lastname@example.org
Published online: 22 November 2017
This paper will focus on the study and identifying various threshold values for two commonly used edge detection techniques, which are Sobel and Canny Edge detection. The idea is to determine which values are apt in giving accurate results in identifying a particular leukemic cell. In addition, evaluating suitability of edge detectors are also essential as feature extraction of the cell depends greatly on image segmentation (edge detection). Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML) is chosen due to its diagnosing which were found lacking. Next, for an enhancement in image quality, noise filters are applied. Hence, by comparing images with no filter, median and average filter, useful information can be acquired. Each threshold value is fixed with value 0, 0.25 and 0.5. From the investigation found, without any filter, Canny with a threshold value of 0.5 yields the best result.
© The Authors, published by EDP Sciences, 2017
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