Detection and Interpretation of Text Information in Noisy Video Sequences

Text superimposed on the video frames provides supplemental but important information for video indexing and retrieval. The detection and recognition of text from video is thus an important issue in automated content-based indexing of visual information in video archives. Text of interest is not limited to static text. They could be scrolling in a linear motion where only part of the text information is available during different frames of the video. The problem is further complicated if the video is corrupted with noise. An algorithm is proposed to detect, classify and segment both static and simple linear moving text in complex noisy background. The extracted texts are further processed using averaging to attain a quality suitable for text recognition by commercial optical character recognition (OCR) software