Near-optimal skin-color detection method under Gaussian frame

In order to solve the problem that the performance is better only when the existing method under the Gaussian frame is in a certain specific interval of false positive rates (FPRs), the invention provides a near-optimal skin-color detection method under the Gaussian frame, which is called as multiple Gaussian models (MGMs) and deduces a discrete and continuous form. The method has good performance for the whole FPR interval and comprises the following steps of: firstly carrying out space normalization on RGB (Red-Green-Blue) colors to obtain an RGB space, then establishing a plurality of optimal single Gaussian models, and finally fusing the optimal models. The MGMs comprise the optical single Gaussian models, and each Gaussian model corresponds to a predefined FPR value. Under the condition of each FPR, the corresponding optimal model can obtain highest true positive rates (TPRs), and the model is solved and obtained by adopting an optimization problem based on a search algorithm. Therefore, for all the FPR values, the MGMs can obtain the near-optimal skin-color detection performance under the Gaussian frame. In addition, the MGMs and the single Gaussian models (SGMs) have the same computational complexity at the test link.