Tensor Voting Based Text Localization in Natural Scene Images

Abstract

A new and efficient text localization method by tensor voting is proposed. Tensor voting is used to extract the text line information based on the observation that the text characters are situated close together and arranged in a line or on a smooth curve. The text line information is useful to reduce the false positive rate in region-based text localization methods. The experimental results obtained for different types of natural text images show that the proposed method successfully detects the text regions with a low false-positive rate.