Fast Uyghur Text Detection in Videos Based on Learning of Baseline Feature

Text detection in image is always a significant part in image semantic understanding, and detection of Uyghur text is a special and extensible application. In this paper, we propose a Uyghur text detection on the basis of the learning of a baseline structure, which generated from texture feature of the text. Firstly, texture features of the image are extracted and texts are classed by a SVM classifier, and then the baseline of the text is structured and represented. Finally, another SVM classifier is trained for Uyghur text detection. The experimental results on user- built dataset including news, entertainment videos and movies show that the proposed algorithm is fast and effective, and better than several typical approaches.