关键词: 文本定位, 文本识别, 连通域, 分类与回归决策树

Abstract:  A novel Chinese text localization method based on Adaboost in natural images is proposed in this paper. Firstly, the text regions are detected using the edge feature, where digital image is processed by edge extraction and binarization, then connected domain analysis is used to remove non-text regions and get candidate text regions. Secondly, a strong classifier of Adaboost with CART（Classification And Regression Tree） is constructed by using the four classes Chinese text features that are extracted by analyzing the text areas. Finally, the correct text areas are got after the candidate regions are send into the strong classifier. The experimental results show that not only can this method achieve a good effect on the text location in the natural images including the images with text of various fonts, sizes and colors but also realize high recall rate and precision rate.

Key words: text location, text recognition, connected domain, classification and regression tree