Arbitrary Shape Scene Text Detection With Adaptive Text Region Representation

Scene text detection attracts much attention in computer vision, because it can be widely used in many applications such as real-time text translation, automatic information entry, blind person assistance, robot sensing and so on. Though many methods have been proposed for horizontal and oriented texts, detecting irregular shape texts such as curved texts is still a challenging problem. To solve the problem, we propose a robust scene text detection method with adaptive text region representation. Given an input image, a text region proposal network is first used for extracting text proposals. Then, these proposals are verified and refined with a refinement network. Here, recurrent neural network based adaptive text region representation is proposed for text region refinement, where a pair of boundary points are predicted each time step until no new points are found. In this way, text regions of arbitrary shapes are detected and represented with adaptive number of boundary points. This gives more accurate description of text regions. Experimental results on five benchmarks, namely, CTW1500, TotalText, ICDAR2013, ICDAR2015 and MSRA-TD500, show that the proposed method achieves state-of-the-art in scene text detection.

1. Introduction

Text is the most fundamental medium for communicating semantic information. It appears everywhere in daily life: on street nameplates, store signs, product packages, restaurant menus and so on. Such texts in natural environment are known as scene texts. Automatically detecting and recognizing scene texts can be very rewarding with numerous applications, such as real-time text translation, blind person assistance, shopping, robots, smart cars and education. An end-to-end text recognition system usually consists of two steps: text detection and text recognition. In text detection, text regions are detected and labeled with their bounding boxes. And in text recognition, text information is retrieved from the detected text regions. Text detection is an important step for end-to-end text recognition, without which texts can not be recognized from scene images. Therefore, scene text detection attracts much attention these years.