A novel text detection and localization method based on corner response

Information of text in videos and images plays an important role in semantic analysis. In this paper, we propose an effective method for text detection and localization in noisy background. The algorithm is based on corner response. Compared to non-text regions, there often exist dense edges and corners in text regions. So we can get relatively strong responses from text regions and low responses from non-text regions. These responses provide us useful cues for text detection and localization in images. Then using a simple block based threshold scheme, we get candidate regions for text. These regions are further verified by combining other features such as color and size range of connected component. Finally, text line is located accurately by the projection of corner response. The experimental results show the effectiveness of our methods.