Open Access Open Access  Restricted Access Subscription or Fee Access

Krystal in Embedding to a Skin Tone Detection Algorithm

B.M. Alaudeen, Dr.G. Tholkappia Arasu

Abstract


Challenges face biometrics researchers and particularly those who are dealing with skin tone detection include choosing a color space, generating the skin model and processing the obtained regions to fit applications. The majority of existing methods have in common the de-correlation of luminance from the considered color channels. Luminance is underestimated since it is seen as the least contributing color component to skin color detection The advantages of the approach are the reduction of space dimensionality from 3D, RGB, to 1D space advocating its unfussiness and the construction of a rapid classifier necessary for real time applications. The proposed method generates a 1D space map without prior knowledge of the host image. A comprehensive experimental test was conducted and initial results are presented. This paper also discusses an application of the method to image steganography where it is used to orient the embedding process.

Keywords


Luminance, Color Transform, Skin Tone Detection

Full Text:

PDF

References


M. Corey, F. Farzam and J.H. Chong, The effect of linearization of range in skin detection, in: Proceedings of IEEE International Conference on Information, Communications and Signal Processing, Singapore, 10-13 December 2007, pp. 1-5.

U.A. Khan, M.I. Cheema and N.M. Sheikh, Adaptive video encoding based on skin tone region detection, in: Proceedings of IEEE Students Conference, Pakistan, 16-17 August 2002, vol (1), and pp. 129-34.

A. Abadpour and S. Kasaei, Pixel-based skin detection for pornography filtering, Iranian Journal of Electrical and Electronic Engineering, 1(3) (2005) 21-41.

J.B. Martinkauppi, M.N. Soriano and M.H. Laaksonen, Behavior of skin color under varying illumination seen by different cameras at different color spaces, in: Proc. of SPIE, Machine Vision Applications in Industrial Inspection IX, USA, 2001, vol. 4301, pp. 102-113.

S. L. Phung, A. Bouzerdoum and D. Chai, Skin segmentation using color pixel classification: analysis and comparison, IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(1) (2005) 148-154.

R.L. Hsu, M. Abdel-Mottaleb and A.K. Jain, Face detection in color images, IEEE Trans. Pattern Analysis and Machine Intelligence, 24(5)(2002) 696-702.

Cryptology and Circumvention, 2003, http://www.frontlinedefenders.org/manual/en/esecman/chapter3_4.html.

A. K. Jain and U. Uludag, Hiding fingerprints minutiae in images, in: Proceedings of Workshop on Automatic Identification Advanced Technologies, New York, 2002, pp.97-102.

C.C. Chang, Y.S. Hu and T.C. Lu, A watermarking-based image ownership and tampering authentication scheme, Pattern Recognition Letters, 27(5)(2006) 439-446.

D. C. Lou, M.C. Hu and J.L. Liu, Multiple layer data hiding scheme for medical images. Computer Standards and Interfaces, 31(2) (2009) 329-335.

A. Brown, 1996, S-Tools, .

A. Westfeld, 2001, F5, .

H. Hioki, A data embedding method using BPCS principle with new complexity measures, in: Proceedings of Pacific Rim Workshop on Digital Steganography, Japan, July 2002, pp.30-47.

A. Cheddad, J. Condell, K. Curran and P. Mc Kevitt, Biometric inspired digital image steganography, in: Proceedings of the 15th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS’08), Belfast, 2008, pp. 159-168.

X. Li, T. Yuan, N. Yu, and Y. Yuan, Adaptive color quantization based on perceptive edge protection, Pattern Recognition Letters, 24(16)(2003)3165-3176.

D. Xu, X. Li, Z. Liu and Y. Yuan, Cast shadow detection in video segmentation, Pattern Recognition Letters, 26(1) (2005)91-99.

X. Li, Image retrieval based on perceptive weighted color blocks, Pattern Recognition Letters, 24(12) (2003)1935-1941.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.