AUTHORS: Idoko John Bush, Rahib Abiyev, Mohammad Khaleel Ma’aitah

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ABSTRACT: Skin colour detection has been a commendable technique due to its wide range of application in both analyses based on diagnostic and human computer interactions. Various problems could be solved by simply providing an appropriate method for pixel-like skin parts. Presented in this study is a colour segmentation algorithm that works directly in RGB colour space without converting the colour space. Genfis function as explored in this study formed the Sugeno fuzzy network and utilizing Fuzzy C-Mean (FCM) clustering rule, clustered the data and for each cluster/class a rule is generated. Also, the Radial Basis Function (RBF) utilized Gaussian function for grouping. Finally, corresponding output from data mapping of pseudopolynomial is obtained from input dataset to the adaptive neuro fuzzy inference system (ANFIS), while the Euclidean distance performed data mapping in the RBF model. The result obtained from these two algorithms depicts the RBFN outperforming ANFIS with remarkable margins.

KEYWORDS: Skin, nonskin, adaptive neuro fuzzy inference system, radial basis function.

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