A bag-of-features approach based on Hue-SIFT descriptor for nude detection

Most of previous papers about the detection of nude or pornographic images start by the application of a skin detector followed by some kind of shape or geometric modeling. In this work, these two steps are avoided by a bag-of-features (BOF) approach, in which images are represented by histograms of sparse visual descriptors. BOF approaches have been applied successfully to object recognition tasks, but most descriptors used in that case are based on gray level information. Our approach is based on an extension to the well-known SIFT descriptor - called Hue-SIFT - aimed at adding color information to the original SIFT. Experimental results show recognition rates which are similar to those achieved by other approaches in literature, without the need for sophisticated skin or shape models.

[1]  Huicheng Zheng,et al.  Blocking objectionable images: adult images and harmful symbols , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[2]  Chang-Hsing Lee,et al.  An adult image identification system employing image retrieval technique , 2007, Pattern Recognit. Lett..

[3]  Koen E. A. van de Sande,et al.  Evaluation of color descriptors for object and scene recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  James M. Rehg,et al.  Statistical Color Models with Application to Skin Detection , 2004, International Journal of Computer Vision.

[5]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[6]  Pau-Choo Chung,et al.  The Adult Image Identification Based on Online Sampling , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[7]  Mario A. Nascimento,et al.  SNIF: a simple nude image finder , 2005, Third Latin American Web Congress (LA-WEB'2005).

[8]  Zhouyu Fu,et al.  Recognition of Pornographic Web Pages by Classifying Texts and Images , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Hermann Ney,et al.  Bag-of-visual-words models for adult image classification and filtering , 2008, 2008 19th International Conference on Pattern Recognition.

[10]  Bo Xu,et al.  Recognition of blue movies by fusion of audio and video , 2008, 2008 IEEE International Conference on Multimedia and Expo.

[11]  Dan Roth,et al.  Learning to detect objects in images via a sparse, part-based representation , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Bin Li,et al.  Region-based Pornographic Image Detection , 2005, 2005 IEEE 7th Workshop on Multimedia Signal Processing.

[13]  Zhen Li,et al.  Pornographic Images Detection Based on CBIR and Skin Analysis , 2008, 2008 Fourth International Conference on Semantics, Knowledge and Grid.

[14]  Seong-Joon Yoo.  Intelligent Multimedia Information Retrieval for Identifying and Rating Adult Images , 2004, KES.

[15]  Yang Liu,et al.  IMAGE GUARDER: AN INTELLIGENT DETECTOR FOR ADULT IMAGES , 2003 .

[16]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[17]  Chong-Wah Ngo,et al.  Evaluating bag-of-visual-words representations in scene classification , 2007, MIR '07.

[18]  N. Goodwin,et al.  Learning to Detect Objects in Images via a Sparse, Part-Based Representation , 2004 .

[19]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[20]  Alan Wee-Chung Liew,et al.  Information-Based Color Feature Representation for Image Classification , 2007, 2007 IEEE International Conference on Image Processing.

[21]  Shuming Zhou,et al.  An algorithm of pornographic image detection , 2007, Fourth International Conference on Image and Graphics (ICIG 2007).

[22]  David A. Forsyth,et al.  Finding Naked People , 1996, ECCV.