Automatic text extraction from video for content-based annotation and retrieval

Efficient content-based retrieval of image and video databases is an important application due to rapid proliferation of digital video data on the Internet nod corporate intranets. Text either embedded or superimposed within video frames is very useful for describing the contexts of search, automatic video lagging, and video cataloging. We have developed a scheme for automatically extracting text from digital images and videos Sor content annotation and retrieval. In this paper we present our approach to robust text extraction fi-om video frames. which carl handle complex image backgrounds, deal with different font sizes, font styles, and font appearances such as normal and inverse video. Our algorithm results in segmented characters that can be directly processed by an OCR system to produce ASCII text. Results from our experiments with over 5000 frames obtained from twelve MPEG video streams demonstrate the good performance of our system in terms of text text identification accuracy and computational efficiency.