An objectionable image detection method based on movement invariants and clustering

Abstract

The phenomenon that objectionable contents spread over the Mobile Internet reflects badly both on users and business. To cope with the situation here, we have proposed a relatively effective and efficient method. Combined with the conventional skin color detection and face detection, we add movement invariants to revise the detection ability and use image clustering based on MPEG-7 to improve the efficiency of human examination and verification. Simulations have shown the good performance for the realtime detection effects, and reduced the misstatement Rate and 90% artificial workload, which improve the detection ratio to a large scale. © Springer-Verlag Berlin Heidelberg 2013.