Text Identification in Complex Background Using SVM

This paper presents a fast and robust algorithm to identify text in image or video frames with complex backgrounds and compression effects. The algorithm first extracts the candidate text line on the basis of edge analysis, baseline location and heuristic constraints. Support Vector Machine (SVM) is then used to identify text line from the candidates in edge-based distance map feature space. Experiments based on large amount of images and video frames from different sources showed the advantages of this algorithm compared to conventional methods in both identification quality and computation time.