
Abstract—With the population of Internet around the world, email has become one of the main methods of communication among people. Due to the flood of online information, great amount of the spam emails brings troubles to people. The number of technical approaches of spam filtering are increasing which are mostly based on the text spam filtering technologies. But it is not very effective for test messages imbedded into images which are developing rapidly in recent years. In this paper, we propose an approach of spam image filtering. Our approach combines the characteristics of spam images with the corner point density to detect spam images. The effectiveness of the proposed approach is experimentally evaluated.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
