Training feedforward neural networks using hybrid particle swarm optimization and gravitational search algorithm for Skin Color Segmentation
نویسندگان
چکیده
The applications of skin color recognition are extended in utilizations both in content based analysis and human computer interactions. Therefore, achieving a useful method for segment the skinlike pixels can help the presented problems. In this paper a hybrid PSOGSA -ANN is proposed as a new training method for Feed forward Neural Networks (FNNs) in order to investigate a high efficiency for solving the skin classification problem. The proposed color segmentation algorithm is applied directly on RGB color space with no need for color space conversion. Experimental results show that the proposed method can increase the performance of the MLP algorithm for the skin color recognition problem in significantly.
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تاریخ انتشار 2014