Image Spam Identifying Algorithm Based on Color and Corner Feature
Yong Wang · Jisuanji gongcheng · 2009
Spammers embed spam message into images and failed many text-based anti-spam systems.This paper proposes an effective method to discriminate the spam images by analyzing the features of image.Most of spam images are generated by computer,which are not as rich in colors as nature photos.Besides,as contained many texts,the images had certain regularity in corner angle distribution.The algorithm extracts some features of color and corner of image,and identifies spam image by a SVM classifier.Experimental result on a real word data shows that the accuracy rate of the proposed algorithm is more than 98%.