Accurate scene text recognition based on recurrent neural network

Abstract

Scene text recognition is a useful but very challenging task due to uncontrolled condition of text in natural scenes. This paper presents a novel approach to recognize text in scene images. In the proposed technique, a word image is first converted into a sequential column vec­tors based on Histogram of Oriented Gradient (HOG). The Recurrent Neural Network (RNN) is then adapted to classify the sequential feature vectors into the corresponding word. Compared with most of the existing methods that follow a bottom-up approach to form words by grouping the recognized characters, our proposed method is able to recognize the whole word images without character-level segmentation and recogni­tion. Experiments on a number of publicly available datasets show that the proposed method outperforms the state-of-the-art techniques signifi­cantly. In addition, the recognition results on publicly available datasets provide a good benchmark for the future research in this area.