Video caption image enhancement for an efficient character recognition

For improved recognition of videotexts, we have focused on image enhancement techniques. Since the videotexts are low-resolution and mixed with complex backgrounds, image enhancement is a key to successful recognition of the videotexts. Especially in Hangul characters, several consonants cannot be distinguished without sophisticated image enhancement techniques. In the paper, after multiple videotext frames containing the same captions are detected and the caption area in each frame is extracted, five different image enhancement techniques are serially applied to the image: multi-frame integration, resolution enhancement, contrast enhancement, advanced binarization, and morphological smoothing operations. We have tested the proposed techniques with the video caption images containing both Hangul and English characters from various video sources such as cinema, news, sports, etc. The character recognition results are greatly improved by using enhanced images in the experiment.

[1]  Jongmin Yoon,et al.  Comparison of Feature Performance and Its Application to Feature Combination in Off-Line Handwritten Korean Alphabet Recognition , 1998, Int. J. Pattern Recognit. Artif. Intell..

[2]  David Doermann,et al.  Text enhancement in digital video , 1999, Electronic Imaging.

[3]  Mohamed S. Kamel,et al.  Extraction of Binary Character/Graphics Images from Grayscale Document Images , 1993, CVGIP Graph. Model. Image Process..

[4]  Ellen K. Hughes,et al.  Video OCR for digital news archive , 1998, Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database.