Statistical skin color detection method without color transformation for real-time surveillance systems

Skin color is the significant information for many emerging applications in surveillance systems. However, the common skin color models usually need to perform color space transformation. This is not suitable for direct hardware implementation. This paper develops a statistical skin color model using the default RGB color space, which is especially suitable to implement on hardware for image processing applications. Moreover, an efficient face detection system is also proposed with our skin color model for hardware implementation. Compared with other skin color models, the proposed model produces the highest detection rate. Furthermore, the extended face detection system also significantly decreases the computational cost of the hardware implementation based on our skin color model. Experimental results demonstrate that our proposed detection system can be easily implemented on a field-programmable gate array (FPGA), where only 3202 logic cells is occupied with the high detection rate.