Internet enterprises generally have needs for monitoring images. For example, illegal items inevitably appear, such as weapons and drugs, in the online trading at an electronic commerce platform such as Taobao.com. There is a need to ensure that the uploaded images comply with the laws and regulations. The traditional method for item monitoring is to monitor text information such as the item name and textual description of the item. To avoid being detected, violators often use implicit, unclear language or hints to describe the illegal items. This situation brings a lot of troubles to a platform like Taobao.com to monitor the items.
Currently, there is already theory for basic image filtering, the basis of which is the image recognition technology. In practice, however, there are still many problems. For example, certain known software provides aggressive pornographic image monitoring technology based on image recognition. Such software identifies images that may include large portion of naked skins based on segmentation of skin colors. The advantage of such software is that it can aggressively block pornographic images. But as it is based on segmentation of skin color, it is likely to identify non-pornographic images as pornographic images. The error rates are quite high.
The image recognition technology itself is an immature research field. How to effectively and efficiently model different image contents still puzzles researchers. Even for the classification of pornographic images which is a relatively mature research field, there are still no satisfactory practical effects. While in the application fields of online trading, the objects being monitored are not limited to pornographic images, books, drugs, weapons, identification documents, cosmetics, and etc., as images from different fields can all become monitored objects. In addition, as the speed of change of the images that need to be monitored for online trading is very fast, traditional filtering technology based on image recognition is not sufficient for applications in the online trading.
The current filtering technologies based on image recognition, because of the low accuracy rate, cannot satisfy the commercial applications in online trading.