研究期間：10208~10307;3D real scene optical character recognition attracts the attention of many researchers which becomes an important research topic recently. In the past, 3D real scene character recognition lies mainly on the analysis of static image or picture. However, mobile hand-held devices or vehicle recoders have widely spread into our daily-life. Hence, the demand for the recognition of 3D characters in videos undergoing moving environments drastically increases. It can be employed in the recognition of characters embedded in road signs, buildings, or license plates in traffic surveillance systems. However, the challenges encountered in 3D moving environments are much more severe, such as poor image quality, noises generated due to the vibration or blurring of capturing devices, etc. They will more or less hinder the success of character recognition. To conquer these problems, we plan to develop an intelligent 3D real scene character recognition system especially devised for characters embedded in moving environments. In our system, it first extracts characters from moving videos. Then, delimit character blocks which contain clear character images through scene analysis and character characteristics for later recognition purpose. This project is a three-years project. In the first year, we will tackle the characters embedded in moving objects captured by static mobile devices. In the second year, the characters to be recognized are embedded in static objects captured by moving devices (such as cars). In the third years, we plan to extract and recognize the characters embedded in moving objects captured by moving devices. Moreover, the works accomplished in the three years will also be integrated to complete an intact 3D real scene character recognition system.
