SVM output score based text line refinement for accurate text localization
Cheolkon Jung, Qifeng Liu, Joongkyu Kim · IEEE International Conference on Acoustics Speech and Signal Processing · 2008
In this paper, we propose the text line refinement method based on the SVM (support vector machine) output score for accurate text localization. In general, SVM output scores for the verification of text candidates provide a measure of the closeness to the text. Up to the present, most researchers used the score for the verification of the text candidate region. However, we use the output score for refining the initial text localization results. By means of the proposed approach, we can obtain more accurate text localization results. The effectiveness and efficiency of the proposed method is validated by extensive experiments on a complex database containing 435 images.