Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : Anu S S | Manju G Suresh

Volume 02 Issue 11  Year 2015 

ISSN no: 2348-3121  

Page no: 32-37

Abstract Skin cancer is found common in humans. It is said as a deadly type of cancer. Most of the skin cancers are curable at initial stages. Although early detection of skin cancer helps from mortality since the early diagnosis of skin cancer is not a reality. The paper presents an automated approach which uses ANN working on the DWT domain of the images aiding the detection of skin cancer. DWT which is a transformation technique helps in decomposition of images. By applying Wavelet Transformation to the input histopathological image and by choosing a group of sub-bands best defect detection is done. The wavelet technique has helped for the decomposition and the original image is reconstructed without any distortion. The effective features of the skin will be taken from the reconstructed image for classification. The pathological background shows one of the main component which gives color to the skin is melanin. The increased value of melanin leads to cancerous one. In image processing the increased melanin is revealed as the increased number of pixels. By taking the histogram of the image this increased melanin content is revealed and using GLCM technique as feature extraction the melanin content is shown by extracting the feature contrast. The GLCM technique also extracts features energy and homogeneity and also from the histogram of the images another feature histogram melanin ratio is estimated. The advantage of lesser computation complexity attributed to the usage of artificial neural network as the classifier offers the proposed system to be relaxed in standalone mode. The proposed algorithm is validated on the set of cancerous and non-cancerous images.

Keywords Histopathological Images; DWT; GLCM; Artificial Neural Network


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