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Noise Removal on Thermal Image and Skin Disease Detection


Jayprakash S. Yadav , National Institute of Electronics and IT, aurangabad ; Mr. Lakshman K., National Institute of Electronics and IT, aurangabad


Thermal Image, Skin Diseases, Kurtosis, Skewness, Entropy, ANN


A new approach is proposed to distinguish the disease of skin from thermal camera imaging. The thermal camera captures the temperature distribution of skin and is employed in various medical applications. The method is based on the disease detection with self- organized neural network and features of the disease image. As the thermal images are more affecting with noise, so in this paper we present an algorithm to remove the noise present in the image. In thermal camera imaging, the selection of filter depends on the purpose of the processing, e.g. edge detection or detection of objects in complex images. Noise filter processes are proceeding in two steps. First detect the noise of the thermal image and second detecting only the noise affected point of the image and use noise removal technique for noise separation from thermal image. In this paper we are using Fast Median Base Filter to detect noisy pixels. This process is fast as compare to normal filter. The performance of filter was evaluated using peak signal to noise ratio and mean absolute error. The noise free image goes through segmentation and feature extraction. The experimental image, features data compare with the existing data base collection and shown the final result.

Other Details

Paper ID: IJSRDV5I50862
Published in: Volume : 5, Issue : 5
Publication Date: 01/08/2017
Page(s): 686-690

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