This paper presents a novel scheme for Chinese text recognition in images and videos. It’s different from traditional paradigms that binarize text images, fed the binarized text to an OCR engine and get the recognized results. The proposed scheme, named grayscale based Chinese Image Text Recognition (gCITR), implements the recognition directly on grayscale pixels via the following steps: image text over-segmentation, building recognition graph, Chinese character recognition and beam search determination.
The advantages of gCITR lie in: (1) it does not heavily rely on the performance of binarization, which is not robust in practical and thus severely affects the performance of OCR, (2) grayscale image retains more information of the text thus facilitates the recognition. Experimental results on text from 13 TV news videos demonstrate the effectiveness of the proposed gCITR, from which significant performance gains are observed.