Text Extraction On Video And Its Application

Text is part of the important information in videos. Text detection and recognition in videos can help a lot in video content analysis and understanding, since text can provide concise and direct description of the stories presented in the videos. In digital news videos, the superimposed captions usually present the involved person's name and the summary of the news event. Hence, the recognized text can become a part of index in a video retrieval system. The importance of video can be estimated by the recognized text. So text detection and analysis is important in video analysis. Detecting the accurate position of text in the video and segmenting text from the complex background are the foundation of video text analysis.The text information extraction system can be divided into the following six parts: text detection, text localization, text tracking, text extraction, text enhancement and text recognition. This thesis focuses on the research in text localization. The projection analysis of edge based method and the learning of support vector machine based method are combined to localize text on videos. It has shown good results in the experiments compared to the simple edge based method and the learning based method. The text localization can be divided into two steps. In the first step, the potentially text area are extracted by the edge method. In the second step, support vector machine is used to classify the actual text areas and the false text areas. The false text areas are removed in this step. This method improves the precision rate of text areas. Compared to the learning based method, this method doesn't need to compute the texture of the whole image. Instead, it only computes the texture of the text areas. This algorithm can reduce the time complexity. The textures used in the support vector machine are wavelet, corner, line and the center of gravity of the text areas.This method is applied in localizing text in advertisements. A multi-resolution based method is used to localize text in advertisements. It is a part of the advertisements detection system. It is obvious that texts in the news are more formal and its positions of texts are in a certain areas. But texts in the advertisements are different from each other in size and style. The method can give out a more accurate position of advertisements. And it has shown good results in the experiments.