Adjed, F. and Faye, I. and Ababsa, F. and Gardezi, S.J. and Dass, S.C. (2016) Classification of skin cancer images using local binary pattern and SVM classifier. In: UNSPECIFIED.
Full text not available from this repository.Abstract
In this paper, a classification method for melanoma and non-melanoma skin cancer images has been presented using the local binary patterns (LBP). The LBP computes the local texture information from the skin cancer images, which is later used to compute some statistical features that have capability to discriminate the melanoma and non-melanoma skin tissues. Support vector machine (SVM) is applied on the feature matrix for classification into two skin image classes (malignant and benign). The method achieves good classification accuracy of 76.1 with sensitivity of 75.6 and specificity of 76.7. © 2016 Author(s).
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 16; Conference of 4th International Conference on Fundamental and Applied Sciences, ICFAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125141 |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 16:18 |
Last Modified: | 09 Nov 2023 16:18 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/6674 |