A decade: Review of scene text detection methods

Abstract

The rapid development of scene text detection shows us the need for text recognition in a scene image. Road signs recognition, reading the scene image for machine translation, text recognition on commercial products, billboards, and vehicle plates are examples of text recognition on natural images. This review discussed the related research of scene text detection in the last ten years. We analysed the past strategies in scene text detection, the strengths and the weaknesses of each method. Additionally, we showed the relationship between text detection methods before and after using deep learning. Scene text detection has evolved to detect horizontal text, multi-orientation, multilingual, curved text, and arbitrary-shaped text. Researchers have proposed various methods to address this need. We evaluate the capability of the proposed framework based on the testing results of several representative benchmark datasets. This review aims to obtain opportunities or proposals to improve the existing accuracy, speed, or generalization cases (the various condition of the text appearances). We present future trends for scene text detection research to complete the review.