TY  - JOUR
T1  - New Segmentation Method for Skin Cancer Lesions
AU - Faisal, Zahraa AU - K. El Abbadi, Nidhal 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 21
SP  - 5598
EP  - 5602
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.5598.5602
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.5598.5602
KW  - Segmentation
KW  -image processing
KW  -edges
KW  -YUV
KW  -Otsu’s
KW  -morphological operation
AB  - Skin cancer lesioning one of the most skin lesions which cause death. Lesion segmentation is a very
important step prior to detecting and classifying the skin cancer. In this study, we introduce a new method to
extract the lesion from the surrounding of healthy skin. The proposed method starts with image preprocessing
included image de-noising and removing the unwanted objects such as thin hair and air bubble by using the
median filter, followed with edge detection using the Markov and Laplace filter. The current algorithm converts
the color image to YUV color space and select the U channel for processing. Thick hair is removed
from U channel by combining both morphological operation and median filter. Mathematical morphology such
as close used to join narrow breaks regions in an object, fill the small holes and remove small objects. The final
step is to find threshold based on Otsu’s thresholding to separate the image to two regions one for lesion and
the other for skin. The result image is binary image or can be color lesion with black background. The accuracy
of the suggested method reaches up to 98%. The algorithm is tested with segmented images by an expert and
give very promised results in many cases gives better results. Also hamming distance is imeasured and it was
better value compared with other algorithms.
ER  -