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Text information in natural scene images serves as important clues for many image-based applications such as scene understanding, content-based image retrieval, assistive navigation, and automatic geocoding. However, locating text from a complex background with multiple colors is a challenging task. In this paper, we explore a new framework to detect text(More)
Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection,(More)
Independent travel is a well-known challenge for blind and visually impaired persons. In this paper, we propose a proof-of-concept computer vision-based wayfinding aid for blind people to independently access unfamiliar indoor environments. In order to find different rooms (e.g. an office, a laboratory, or a bathroom) and other building amenities (e.g. an(More)
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 algorithm is able to model both character appearance and structure to generate representative and discriminative text descriptors. The contributions of this paper include three(More)
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 steps: boundary clustering (BC), stroke segmentation, and string fragment classification. In BC, we propose a new bigram-color-uniformity-based method to model both text and(More)
Independent travel is a well known challenge for blind or visually impaired persons. In this paper, we propose a computer vision-based indoor wayfinding system for assisting blind people to independently access unfamiliar buildings. In order to find different rooms (i.e. an office, a lab, or a bathroom) and other building amenities (i.e. an exit or an(More)
There are more than 161 million visually impaired people in the world today, of which 37 million are blind. Camera-based computer vision systems have the potential to assist blind persons to independently access unfamiliar buildings. Signs with text play a very important role in identification of bathrooms, exits, office doors, and elevators. In this paper,(More)