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%.
|Title of host publication||Proceeding of the 4th International Conference of Fundamental and Applied Sciences 2016|
|Publication status||Published - 1 Nov 2016|
|Name||AIP Conference Proceedings|
Adjed, F., Faye, I., Ababsa, F., Gardezi, S. J., & Dass, S. C. (2016). Classification of Skin Cancer Images Using Local Binary Pattern and SVM Classifier. In Proceeding of the 4th International Conference of Fundamental and Applied Sciences 2016  (AIP Conference Proceedings; Vol. 1787, No. 1). AIP Publishing. https://doi.org/10.1063/1.4968145