Preprocessing and Feature Extraction for Psoriasis Images Based on Discrete Wavelet Transform
DOI:
https://doi.org/10.31695/IJERAT.2020.3643Keywords:
Psoriasis Images, Wavelet Transform, Haar Basis Filter, Sharpening, Soble, LaplacianAbstract
This paper, proposes the pre-processing methods use a small neighborhood of a pixel in the input image to get a new brightness value in the output image. Such pre-processing operations are also called filtration. in this paper, we start with the image using a medical case for psoriasis image after change it to gray state implemented under the transform domain (i.e frequency), using wavelet transform then use three filters sharpening, Sobel, and Laplace filter. after make proposed by computing PSNR for each state to show the effect of it. Then extract features through an apply a set of measures (Energy, Entropy, Standard deviation, Variance, Mean) of low low sub-image. The proposed system was implemented on the medical case for psoriasis image dataset, some of them were obtained from the hospitals and the other was obtained from the dataset (Light Field Image of Dataset skin Lesions), available on the Internet and the proposed system implemented in programing language Visual Basic 6.0.
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Copyright (c) 2020 Raniah Ali Mustafa, Haitham Salman Chyad, Rafid Aedan Haleot
This work is licensed under a Creative Commons Attribution 4.0 International License.
