Title :
A New Near-Duplicate Detection System Using Object Semantics for Filtering Image Spam
Author :
Qu, Zhaoyang ; Zhang, Yingjin
Author_Institution :
Sch. of Inf. Eng., Northeast Dianli Univ., Jilin, China
Abstract :
As image spam becomes widespread and does a lot of harm, it is more important to filtering such spam effectively for now. Low accuracy rate and poor recognition of obfuscation techniques are main defects of current anti-image-spam technologies. For solving those problems, this paper proposes a new image spam near-duplicate detection system, applying image object semantics extraction to filter spam. The experimental results show that the system has better filtering performance than previous systems, particularly on higher accuracy rate and better anti-obfuscation effect, and effectively solves the above-mentioned problems.
Keywords :
feature extraction; object detection; unsolicited e-mail; anti-obfuscation effect; image object semantics extraction; image spam filtering; near-duplicate detection system; Cities and towns; Electronic mail; Feature extraction; Image recognition; Information filtering; Information filters; Object detection; Postal services; Shape; Unsolicited electronic mail; image semantics; image spam filtering; object semantics;
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering, 2009 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-0-7695-3876-1
DOI :
10.1109/ICIII.2009.457