Arbitrary shape scene text recognition based on deep learning

Abstract:

One of the challenging in scene text recognition is to deal with distortions or irregular layout. Especially, perspective text and curved text are common in natural scenes and are difficult to recognize. In this paper, we propose an attention enhanced network with flexible rectification function for Arbitrary shape scene text recognition. The network consists of a text rectification network and an attention enhanced recognition network. The rectification network adaptively rectifies the text in the input image to reduce the difficulty recognition. The recognition network is an attention enhanced sequencetosequence model that predicts a character sequence directly from the rectified image. With end to end training approach, only images and corresponding text labels are required. Extensive experiments have been conducted on a variety of open datasets, including SVT, ICDAR 2003 and CUTE80, and the experimental results shows the proposed network has excellent performance.