Document Type
Conference Proceeding
Publisher
IEEE
Faculty
Faculty of Computing, Health and Science
School
School of Engineering and Mathematics / Centre for Communications Engineering Research
RAS ID
3483
Abstract
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
DOI
10.1109/ICICS.2005.1689330
Access Rights
free_to_read
Comments
This is an Author's Accepted Manuscript of: Boussaid , F., Bouzerdoum , A., & Chai, D. K. (2005). VLSI implementation of a skin detector based on a neural network. Proceedings of Fifth International Conference on Information, Communications & Signal Processing. (pp. 1605 - 1608). Thailand. IEEE. Available here
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