Recognition and Investigation of Skin Cancer using Morphological Operations
Prabha Devi D1, Iniya Shree S2
1Prabha Devi D, Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathy (Tamil Nadu), India.
2Iniya Shree S, Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathy (Tamil Nadu), India.
Manuscript received on 17 December 2018 | Revised Manuscript received on 28 December 2018 | Manuscript Published on 09 January 2019 | PP: 474-477 | Volume-7 Issue-4S November 2018 | Retrieval Number: E2054017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In today’s world Skin cancer (Melanoma) has become a very common disease. Melanoma is the cancer cells which exhibit as the abnormal cells from skins that can be developed in any other parts of the body. Over exposure to UV rays is the main cause for Melanoma. Other way that causes Melanoma is the tanning beds. Skin cancers are classified into three different types as follows: Basal-Cell skin Cancer (BCC), squamous-cell skin cancer (SCC) and melanoma. Melanoma causes enormous and irreparable damage. Symptoms incorporate a mole that can change in its volume, contour, and color. The effective way to prevent Melanoma is by decreased exposure to UV rays and tanning beds. The stipulated approach followed by dermatologist is rightful supervision of the Skin. As this approach is time and power consuming, a new feature based classification for the detection of skin in various features of images as described in this paper. This approach reduces the professionals work. The morphological operation is used to differentiate the cancerous cell from the image .The skin texture features are obtained from processed image and used for classification of images as malignant and non-malignant.
Keywords: Morphological Operations, TDS, Melanoma, Features.
Scope of the Article: Pattern Recognition