Gender and Identity Recognition in a Visually Lossless Encoded Image
Keywords:
JPEG2000, Visibility threshold, Bit plane coding, Eigen faces, Discrete Wavelet Transform, Dead Zone QuantizationAbstract
The last decades have experienced astounding growth in the use of images that has resulted in large repositories of images that have to be stored and transmitted, bringing new techniques and standards to compress such data sets efficiently. Lossless, or numerically lossless, methods commonly achieve moderate compression ratios, whereas lossy methods achieve higher compression ratios at the expense of image ï¬delity. Performing recognition algorithms on these compressed images require extraction of original image from the codestream. The goal of this research is to examine the feasibility of implementing gender recognition algorithm and identity recognition algorithm directly into JPEG2000 compressed domain avoiding inverse discrete wavelet transform (IDWT). Such an approach would consequently enable the use of compressed images in recognition purposes, thus reducing both computational time and storage requirements.
References
Han Oh, A.Biligin, M.W. Visually Lossless Encoding for JPEG2000. IEEE Transactions on Image Processing.vol.22,no.1,pp.189-201,2013.
Tsung-Han Tsai and Lian-Tsung Tsai. JPEG2000 encoder architecture design with fast EBCOT algorithm. International Symposium on VLSI Design, Automation and Test.pp.279-282,2005.
A. B. Watson, G. Y .Yang, J. A.Solmon, J.Villasenor , “Visibility of Wavelet quantisation noise”,vol.6,no.8,pp.1164-1175,1990.
D. S. Taubman and M. W. Marcellin, JPEG2000: Image Compression Fundamentals, Standards, and Practice. Boston, MA: Kluwer, 2002.
M. Bolin and G. Meyer, “A perceptually based adaptive sampling algorithm,” in Proc. SIGGRAPH Conf., 1998, pp. 299–309.
A. P. Bradley, “A wavelet visible difference predictor,” IEEE Trans. Image Process., vol. 8, no. 5, pp. 717–730, May 1999.
Z. Liu, L. J. Karam, and A. B. Watson, “JPEG2000 encoding with perceptual distortion control,” IEEE Trans. Image Process., vol. 15, no. 7, pp. 1763–1778, Jul. 2006.
S. G. Mallat, “A theory for multiresolution signal decomposition: The wavelet representation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 7, pp. 674–693, Jul. 1989.
Vignesh Ramanathan , Bangpeng Yaoy , Li Fei-Feiy . “Social Role Discovery in Human Events “, International Conference on Computer Vision and Pattern Recognition(CVPR) ,IEEE,2013 , pp.2475-2482.
H. Sahoolizadeh, Y. A Ghassabeh. “Face recognition using eigen-faces, fisher-faces and neural networks”, Seventh International Conference on Cyberneic Intelligent Systems (CIS), IEEE, 2008,pp.1-6.
K.Delac,H.Grgic,S.Grgic. “Towards Face Recognition in JPEG2000 Compressed Domain”, 6th EURASIP Conference on Speech and Image Processing, Multimedia Communications and Services, IEEE, 2007, pp.148-152. [12]. Sahoolizadeh, J; Electr.Arak; Ghassabeh Y.A., ‘’ Face recognition using eigen-faces,fisher-faces and neural networks’’, 7th IEEE Conference on Cybernetic Intelligence System, 9-10 Sept 2008, pp. 1-6
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
