On image similarity in the context of multimedia social computing

Social multimedia content had an unprecedented increasing trend in recent years, and receiving a number of research attentions. Images, an exceedingly expressive form of social multimedia, can be widely seen in news report for social emergency. Among the vast number of images for social emergency are many repurposed images, that is, variants not interpreted as what the original images express. Such repurposed images appear in many online pages and may mislead the public. This make it being an interesting and challenging task to identify whether an image is repurposed. We propose a novel framework, called SOFC, to identify the repurposed images. A SIFT-based identical parts finding algorithm is used to find and align all potential identical blocks in the repurposed images and the original images. We then compute the similarity of the potential identical blocks by implementing an object-based likelihood measuring algorithm, to determine whether these blocks are identical in the two images. Finally, the effectiveness of the proposed identification method is validated by experiments on a image set of real social emergency.