An Approach to Image Extraction and Accurate Skin Detection from Web Pages

Authors: Moheb R. Girgis, Tarek M. Mahmoud, Tarek Abd-El-Hafeez

Abstract:

This paper proposes a system to extract images from web pages and then detect the skin color regions of these images. As part of the proposed system, using BandObject control, we built a Tool bar named 'Filter Tool Bar (FTB)' by modifying the Pavel Zolnikov implementation. The Yahoo! Team provides us with the Yahoo! SDK API, which also supports image search and is really useful. In the proposed system, we introduced three new methods for extracting images from the web pages (after loading the web page by using the proposed FTB, before loading the web page physically from the localhost, and before loading the web page from any server). These methods overcome the drawback of the regular expressions method for extracting images suggested by Ilan Assayag. The second part of the proposed system is concerned with the detection of the skin color regions of the extracted images. So, we studied two famous skin color detection techniques. The first technique is based on the RGB color space and the second technique is based on YUV and YIQ color spaces. We modified the second technique to overcome the failure of detecting complex image's background by using the saturation parameter to obtain an accurate skin detection results. The performance evaluation of the efficiency of the proposed system in extracting images before and after loading the web page from localhost or any server in terms of the number of extracted images is presented. Finally, the results of comparing the two skin detection techniques in terms of the number of pixels detected are presented.

Keywords: Browser Helper Object, Color spaces, Image and URL extraction, Skin detection, Web Browser events.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084796

References:

[1] Postel, J., "Simple Mail Transfer Protocol", RFC 821, USC/Information Sciences Institute, August 1982.
[2] Postel, J., and Reynolds, J., "File Transfer Protocol (FTP), RFC 959, USC/Information Sciences Institute, October 1985.
[3] Postel, J., and Reynolds, J., "TELNET Protocol Specification", RFC 854, USC/Information Sciences Institute, May 1983.
[4] Postel, J.,"Media Type Registration Procedure", RFC 1590,USC/Information Sciences Institute, March 1994. URL:ftp://ds.internic.net/rfc/rfc1590.txt>
[5] Borenstein, N., and Freed, N., "MIME (Multipurpose Internet Mail Extensions) Part One: Mechanisms for Specifying and Describing the Format of Internet Message Bodies", RFC1521, Bellcore, Innosoft, September 1993. URL:ftp://ds.internic.net/rfc/rfc1521.txt>
[6] Fielding, R.,"Relative Uniform Resource Locators", RFC 1808, June 1995
[7] Frank, H., and Mayer, S., "The Dexter Hypertext Reference Model", Communications of the ACM, pp. 30-39, vol. 37 no. 2, Feb 1994.
[8] http://msdn.microsoft.com/library/default.asp? url=/workshop/ browser/webbrowser/reflist_vb.asp
[9] http://www.microsoft.com/isapi/redir.dll?prd=ie&pver =6&ar=msnhome
[10] Anthony, J., Jim, O., and Lance, O., "Microsoft Network Programming for the Microsoft .NET Framework", Published By Microsoft Press, A Division of Microsoft Corporation, One Microsoft Way Redmond, Washington 98052-6399, Copyright ┬® 2004.
[11] http://www.regexlib.com/
[12] Ilan, A., "An API for Google Image Search", http://www.codeproject.com.
[13] http://slappy.cs.uiuc.edu/fall03/team2/Final/.
[14] P. Peer, F. Solina, "An automatic human face detection method", in Proc. 4th Computer Vision Winter Workshop (CVWW), Rastenfeld, Austria, Feb. 1999, pp. 122-130.
[15] Duan, L., Cui, G., Gao, W., and Zhang, H., "Adult image detection method base-on skin color model and support vector machine". In Asian Conference on computer Vision, pages 797-800, Melbourne, Australia, 2002.
[16] Gonzales R. and Woods R. E., "Digital Image Processing," Prentice Hall, Inc, New Jersey, 2002.
[17] Brand J., Mason J. S., Roach M., Pawlewski M.."Enhancing face detection in colour images using a skin probability map". Int. Conf. on Intelligent Multimedia, Video and Speech Processing, pp. 344-347, 2001.
[18] Forsyth D. A.. Fleek M., and Bregler C.. "Finding naked people". In Proc.Forth European Conference on Computer Vision. pp 593-602. 1996.
[19] Brown, D., Craw, I., & Lewthwaite, J." A SOM Based Approach to Skin Detection with Application in Real Time Systems". In Proc. Of the British MachineVision Conference, 2001.
[20] Chai, D. & Bouzerdoum, A. "A Bayesian Approach to Skin Color Classification in YCbCr Color Space". In Proc. Of IEEE Region Ten Conference, vol. 2, 421- 4124, 1999.
[21] Zarit, B. D., Super, B. J., and Quek, F. K. H. "Comparison of Five Color Models in Skin Pixel Classification". In ICCV-99 Int-l Workshop on recognition, analysis and tracking of faces and gestures in Real-Time systems, 58-63, 1999.
[22] Terrillon, J.-C., Shirazi, M. N., Fukamachi, H., and Akamatsu, S. "Comparative Performance Of Different Skin Chrominance Models and Chrominance Spaces for The Automatic Detection of Human Faces in Color Images". In Proc. of the International Conference on Face and Gesture Recognition, 54-61, 2000.
[23] Brand, J., and Mason, J. "A Comparative Assessment of Three Approaches to Pixel level Human Skin-Detection". In Proc. of the International Conference on Pattern Recognition, vol. 1, 1056-1059, 2000.
[24] Phung, S. L., Bouzerdoum, A. and Chai, D. "Skin Segmentation Using Color Pixel Classification: Analysis and Comparison" , IEEE Tran. On Pattern Analysis and Machine Intelligence, Vol. 27, No. 1, Jan. 2005.
[25] Cho, K. M., Jang, J. H. and Hong, K. S. "Adaptive Skin Color Filter", Pattern Recognition, Vol. 34, pp. 1067-1073, 2001.