SUPER PIXELS AND SKIN COLOR DETECTION USING IMAGE ENCRIPTION

AMIT KUMAR CHANDANAN

Abstract


This paper, which extended our previous work presented a new region-based technique for skin color detection which outperformed the current state-of-the-art pixel-based skin color detection technique on the popular Compaq dataset. Color and spatial distance based clustering technique is used to extract the regions from the images, also known as super pixels followed by a state-of-the-art non-parametric pixel-based skin color classifier called the basic skin color classifier. The pixel-based skin color evidence is then aggregated to classify the super pixels. Finally, the Conditional Random Field (CRF) is applied to further improve the results. As CRF operates over super pixels, the computational overhead is minimal. Our technique achieved 91.17% true positive rate with 13.12% false negative rate on the Compaq dataset tested over approximately 14,000 web images.

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References


R. PK Poudel, H. Nait-Charif, J.J. Zhang, D. Liu.“Region-Based Skin Color Detection”, in VISAPP, 2012.

M.J. Jones,J.M.Rehg.“Statistical colo rmodels with application to skin detection”. International Journal of Computer Vision 46 (2002) 81–96.

P. Kakumanu, S.Makrogiannis, N.Bourbakis. “A survey of skin-color modelling and detection methods”. Pattern Recognition 40 (2007) 1106–1122.

D.A. Socolinsky, A. Selinger,J.D. Neuheisel. “Face recognition with visible and thermal infrared imagery”. Computer Vision and Image Understanding 91 (2003) 72–114.

Z. Pan, G. Healey, M.. Prasad, B. Tromberg. “Face recognition in hyperspectral images”. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 (2003) 1552–1560.

M.H. Yang,N. Ahuja. Detecting human faces in color images”. In International

ACCENT JOURNAL OF ECONOMICS ECOLOGY & ENGINEERING

Peer Reviewed and Refereed Journal IMPACT FACTOR: 2.104 (INTERNATIONAL JOURNAL)

UGC APPROVED NO. 48767

Vol.03, Issue 05, May 2018, Available Online: www.ajeee.co.in/index.php/AJEEE

Paper Id /Ajeee-1302

Conference on Image Processing,1998. Volume1 (1998) 127–130.

H. Kruppa, M. Bauer, B. Schiele. “Skin patch detection in real-world images”. In Van Gool, L.,(Ed.) : Pattern Recognition. Volume 2449 of Lecture Notes in Computer Science. Springer Berlin/Heidelberg (2002)109–116.

B. Jedynak, H. Zheng, M.. Daoudi. “Maximum entropy models for skin detection”. In Energy Minimization Methods in Computer Vision and Pattern Recognition (2003) 180–193.

N. Sebe, I. Cohen, T. Huang, T. Gevers. “Skin detection: A Bayesian network approach”. In Proceedings of the 17th International Conference on Pattern Recognition, Cambridge, UK (2004) 903–906.

A.P. Moore, S. Prince, J. Warrell, U. Mohammed, G. Jones. “Super pixel lattices”. In IEEE Conference on Computer Vision and Pattern Recognition. (2008).

X. Ren, J.Malik. “Learning a classification model for segmentation”. In IEEE International Conference on Computer Vision. Volume1 (2003).

S. Soatto.“Actionable information invision”. In Proceedings of the International Conference on Computer Vision. Volume 25 (2009).

B. Fulkerson, A. Vedaldi, S. Soatto. “Class segmentation and object localization with super pixel neighbourhoods”. In Proceedings of International Conference on Computer Vision. Volume 5 (2009).


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