WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 13, 2017
Intelligent Machine Learning Algorithms for Colour Segmentation
Authors: , ,
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 pseudo-polynomial 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.
Search Articles
Pages: 232-240
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 13, 2017, Art. #26