Skin Cancer Diagnosis using Ostu Thresholding with and Without Bat Algorithm
Gurinder Kaur Sodhi1, S .Chatterji2, Kamal Kant Sharma3

1Gurinder Kaur Sodhi*, Research Scholar , Desh Bhagat University , Mandi Gobindgarh,Punjab , India.
2Dr S .Chatterji, Retired Professor and Head Electrical Engineering Department , NITTTR , Chandigarh , India.
3Dr Kamal Kant Sharma, Associate professor , Electrical Engineering Department , Chandigarh University, Gharaun , India.

Manuscript received on March 28, 2020. | Revised Manuscript received on April 25, 2020. | Manuscript published on April 30, 2020. | PP: 1569-1573 | Volume-9 Issue-4, April 2020. | Retrieval Number: B3651129219/2020©BEIESP | DOI: 10.35940/ijeat.B3651.049420
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Abstract: Nowadays , Cancer diseases is becoming a house hold name but science has exponentially manifold to fight against the deadly disease. Even though ;many cancer diseases are still untouched or not followed properly clinically detected at early stages and lead to incurable disease ,one of the cancer disease termed as Skin Cancer . The main concern is early detection so that it should not be spread to other parts of the body and patient fails to recover . This is not detectable if it’s not known to patient and not informed to concerned doctor at a right time . This manuscript discusses and explains in detail the thresholding technique used for segmentation of the image with and without optimized BAT algorithm.The results have been compared with various already known parameters i.e . Peak Signal to Noise Ratio (PSNR ) , Mean square error (MSE ) and Rand Index (RI) and validated with prior art . Evaluation of Ostu thresholding and Ostu thresholding with BAT algorithm have been compared and analysis has been presented with optimum results have been obtained by applying Ostu thresholding with BAT algorithm as compared with Ostu thresholding algorithm considering various essential parameters.
Keywords: Ostu thresholding technique , BAT algorithm , Skin Cancer , PSNR , RI