Extraction and Recognition Chinese Character of Video Using Wavelet-fractal and Multilevel Classification

Abstract

Extraction and recognition Chinese characters in a video are widely applied to fields like image annotation and retrieval. In this paper, we extract features of Chinese character based on wavelet-fractal and employ multi-level classification including K-means and Back Propagation Neural Network (BPNN) to recognize. we take the projection of image in 0 ◦ ,4 5 ◦ ,9 0 ◦ , 135 ◦ and ring as features. To verify the algorithm, we developed an extraction and recognition Chinese character system consists of text regions detection, tracking, character segmentation, and character recognition module. In the character tracking, by introducing the concepts of density, sliding window and similarity, we design an algorithm of back-searching and forward-searching the frame interval which includes specific text regions. Statistical hypothesis test is employed to segment the characters. Finally, we give full and detailed experiments according to the algorithms proposed in this paper and the results turn out these algorithms are efficient.