Region-based blood color detection and its application to bloody image filtering

Along with the widespread use of the World Wide Web, violent contents have affected our daily life. Although there are some investigations about violence video detection, few methods touch on the problem of violent and gory image detection. In this paper, we propose a region-based blood color detection algorithm. We first extract color and texture features from the detected bloody region of an image. We extract features of the whole image according to the global and local method. These features are fed into the SVM classifier. Experimental results have demonstrated the effectiveness of our proposed algorithm.

[1]  Arnaldo de Albuquerque Araújo,et al.  A bag-of-features approach based on Hue-SIFT descriptor for nude detection , 2009, 2009 17th European Signal Processing Conference.

[2]  Ari Visa,et al.  Efficient Fourier shape descriptor for industrial defect images using wavelets , 2005 .

[3]  Dah-Jye Lee,et al.  Similarity measurement using polygon curve representation and Fourier descriptors for shape-based vertebral image retrieval , 2003, SPIE Medical Imaging.

[4]  Gösta H. Granlund,et al.  Fourier Preprocessing for Hand Print Character Recognition , 1972, IEEE Transactions on Computers.

[5]  David Suter,et al.  Recognition of adult images, videos, and web page bags , 2011, TOMCCAP.

[6]  Cecilia R. Aragon,et al.  A fast contour descriptor algorithm for supernova image classification , 2007, Electronic Imaging.

[7]  Adrian Ulges,et al.  Automatic detection of child pornography using color visual words , 2011, 2011 IEEE International Conference on Multimedia and Expo.

[8]  Abdelmajid Ben Hamadou,et al.  Violent web images classification based on MPEG7 color descriptors , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[9]  Tieniu Tan,et al.  Baseline Results for Violence Detection in Still Images , 2012, 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance.