Robust Text Detection in Natural Scene Images

摘要

Natural scenes of blurred text images are challenges to current text recognition field. In our paper, a novel method for text detection in natural scene image is suggested using edge detection, maximally stable extremal region (MSER) and tensor voting. Edge detection and MSER methods are combined to find the greatest character candidates from stable areas which are extracted from an input image. These text candidates are used to extract the text line information using tensor voting that creates normal vectors and curve saliency values in characters along the text lines. Therefore, the text line information is used to eliminate non-text areas. Our method is evaluated on the ICDAR2013 datasets and experiment results show that the proposed result is compared to the previous methods.