Deep learning networks have recently been shown to outperform other segmentation
methods on various public, medical-image challenge datasets, particularly on metrics …

This paper tackles the problem of recognizing characters in images of natural scenes. In
particular, we focus on recognizing characters in situations that would traditionally not be …

Segmentation of text from badly degraded document images is a very challenging task due
to the high inter/intra-variation between the document background and the foreground text of …

Text information in natural scene images serves as important clues for many image-based
applications such as scene understanding, content-based image retrieval, assistive …

In this paper, we propose a novel framework to extract text regions from scene images with
complex backgrounds and multiple text appearances. This framework consists of three main …

Text detection is important in the retrieval of texts from digital pictures, video databases and
webpages. However, it can be very challenging since the text is often embedded in a …

The problem of document structure reconstruction refers to converting digital or scanned
documents into corresponding semantic structures. Most existing works mainly focus on …

In the paper, we propose a camera-based assistive system for visually impaired or blind
persons to read text from signage and objects that are held in the hand. The system is able …

We propose a camera-based assistive text reading framework to help blind persons read
text labels and product packaging from hand-held objects in their daily lives. To isolate the …

In this paper, we propose a novel algorithm to detect text information from natural scene
images. Scene text classification and detection are still open research topics. Our proposed …