VLSI implementation of a skin detector based on a neural network

This paper describes the VLSI implementation of a skin detector based on a neural network. The proposed skin detector uses a multilayer perception with three inputs, one hidden layer, one output neuron and a saturating linear activation function to simplify the hardware implementation. The skin detector achieves a classification accuracy of 88.76%. To reduce mismatch associated errors, a single skin detection processing unit is used to classify all pixels of the input RGB image. The current-mode fully analog skin detection processing circuitry only performs computations during the read-out phase, enabling real-time processing. Fully programmable, the proposed skin detection processing circuitry allows for the external control of all classifier parameters to compensate for mismatch and changing lighting conditions.