Detecting multilingual text in natural scene

In this paper, a multilingual text detection method is proposed, which focus on finding all of the text regions in natural scene regardless of their language type. According to rules of writing system, three different texture features are selected to describe the multilingual text: histogram of oriented gradient (HOG), mean of gradients (MG) and local binary patterns (LBP). Finally, cascade AdaBoost classifier is adopted to combine the influence of different features to decide the text regions. Experiments conducted on the public English dataset and the multilingual text dataset show that the proposed method is encouraging.