A new colour space for skin tone detection

Authors:
Abbas Cheddad;Joan Condell;Kevin Curran;Paul Mc Kevitt
Affiliations:
School of Computing and Intelligent Systems, Faculty of Computing and Engineering, University of Ulster at Magee, Northern Ireland, United Kingdom;School of Computing and Intelligent Systems, Faculty of Computing and Engineering, University of Ulster at Magee, Northern Ireland, United Kingdom;School of Computing and Intelligent Systems, Faculty of Computing and Engineering, University of Ulster at Magee, Northern Ireland, United Kingdom;School of Computing and Intelligent Systems, Faculty of Computing and Engineering, University of Ulster at Magee, Northern Ireland, United Kingdom
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 7
Cited 1

Automatic Detection of Human Nudes

International Journal of Computer Vision - 1998 Marr Prize
Face Detection in Color Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Does Colorspace Transformation Make Any Difference on Skin Detection?

WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Log-Opponent Chromaticity Coding of Color Space

ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Skin Segmentation Using Color Pixel Classification: Analysis and Comparison

IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Detection for Video Summary Using Illumination-Compensation and Morphological Processing

ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 02
A skin tone detection algorithm for an adaptive approach to steganography

Signal Processing

A dynamic threshold approach for skin tone detection in colour images

International Journal of Biometrics

Quantified Score

Hi-index	0.00

Visualization

Abstract

The majority of existing methods have one thing in common which is the de-correlation of luminance from the considered colour channels. It is believed that the luminance is underestimated here since it is seen as the least contributing colour component to skin colour detection. This work questions this claim by showing that luminance can be useful in separating skin and non-skin clusters. To this end, this work uses a new colour space which contains error signals derived from differentiating the grayscale map and the non-encoded-red grayscale version. The advantages of this approach are the reduction of space dimensionality from 3D to 1D space and the construction of a rapid classifier necessary for real time applications. This method is meant to assist digital image steganography to orient the embedding process since skin information is deemed to be psycho-visually redundant.