Detecting of Vertically-Oriented Texts in Images Containing Natural Scenes

Abstract

Universally, scene text in natural images is an expressive means of communication. Texts available in an image could provide important information which can enhance the interpretation of the image, for instance texts on product packages and road signs. Recently, scene texts detection has been recognized as an important research field in computer vision. However, texts detection in natural scene images has been challenging due to the complicated scene background involving varying fonts, sizes, image resolutions etc. As to date, different methods of detecting texts in natural scene images have been proposed for horizontal texts, arbitrarily-oriented texts and curved texts, but there is a lack of detection of vertically-oriented texts in the natural scene images. Hence, this research proposed a framework for detecting the top-to-bottom, bottom-to-top and horizontally-stacked vertical texts in natural scene images. In this paper, Multi-directional Text Detector (MTD) is modelled and developed to locate the vertically-oriented texts in natural scene images, and the Vertical Scene Texts Dataset-700 (VSTD-700) is developed. The preliminary testing shows that the success rate of detection of MTD is 87% on ICDAR 2013, 73% on ICDAR 2015, 71% on MSRA-TD500 and 87% on VSTD-700 datasets. Hence, the results showed that MTD is able to detect vertically-oriented texts on top of the horizontally-oriented and arbitrarily-oriented texts in natural scene images simultaneously.