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Detection of Cancerous and Non-cancerous Skin by using GLCM Matrix and Neural Network Classifier

by Md. Al-Amin, Mohammad Badrul Alam Miah, Md. Ronju Mia
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 132 - Number 8
Year of Publication: 2015
Authors: Md. Al-Amin, Mohammad Badrul Alam Miah, Md. Ronju Mia
10.5120/ijca2015907513

Md. Al-Amin, Mohammad Badrul Alam Miah, Md. Ronju Mia . Detection of Cancerous and Non-cancerous Skin by using GLCM Matrix and Neural Network Classifier. International Journal of Computer Applications. 132, 8 ( December 2015), 44-49. DOI=10.5120/ijca2015907513

@article{ 10.5120/ijca2015907513,
author = { Md. Al-Amin, Mohammad Badrul Alam Miah, Md. Ronju Mia },
title = { Detection of Cancerous and Non-cancerous Skin by using GLCM Matrix and Neural Network Classifier },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 132 },
number = { 8 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 44-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume132/number8/23618-2015907513/ },
doi = { 10.5120/ijca2015907513 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:28:50.387987+05:30
%A Md. Al-Amin
%A Mohammad Badrul Alam Miah
%A Md. Ronju Mia
%T Detection of Cancerous and Non-cancerous Skin by using GLCM Matrix and Neural Network Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 132
%N 8
%P 44-49
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Day by day the use of image processing is increasing. Now a days image processing is the part and parcel of medical science. By image processing many types of cancer are easily detected. Skin cancer is one of them. In this paper the proposed method detects two types of skin one is cancerous skin and another is affected but not cancerous skin. Skin cancers are most common cancer in human. Skin cancers are curable cancer after early detection. The system can distinguish cancerous skin and non-cancerous skin based on some values of features. Some value extracted from Grey Level Co-occurrence Matrix (GLCM). GLCM features include Contrast, Correlation, Energy, Entropy and Homogeneity. Besides those MajorAxisLength, MinorAxisLength, Solidity, Equivdiameter, Perimeter, Mean, Standard Deviation, ConvexArea, Area, Euclidean Distance, Manhattan Distance, Minkowski Distance and Hamming Distance. There are several steps for evaluating the process. The first step is preprocessing, in this step the noise is removed by using filter. The filtered image is segmented into gray level and black and white (BW) image. All the features are calculated on black and white (BW) image. The neural network is used to classify the images. It is an easy system rather than the doctor biopsy procedure. The system consumes less time and gets better result than ordinary systems.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Skin cancer GLCM Cancer detection Neural Network

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