Concerning the problem that the linear eigentransformation method cannot capture the statistical properties of the nonlinear facial image, a Data-driven Local Eigentransformation (DLE) method for face hallucination was proposed. Firstly, some samples most similar to the input image patch were searched. Secondly, a patch-based eigentransformation method was used for modeling the relationship between the Low-Resolution (LR) and High-Resolution (HR) training samples. Finally, a post-processing approach refined the hallucinated results. The experimental results show the proposed method has better visual performance as well as 1.81dB promotion over method of locality-constrained representation in objective evaluation criterion for face image especially with noise. This method can effectively hallucinate surveillant facial images.
Automatic analysis system of Chinese character structure applies many mature techniques in the fields such as computer vision, image understanding to analyze and recognize the Chinese character. GB2312-80 Chinese characters set was chosen to generate subcomponent images. Then the feature description of Chinese characters component structures is generated, and valid ratio is over 90%.