Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Computing, Health and Science

School

School of Engineering and Mathematics, Centre for Communications Engineering Research

RAS ID

3483

Comments

This conference paper was originally published as: 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. Original article available here

© 2005 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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

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Link to publisher version (DOI)

10.1109/ICICS.2005.1689330