Abstract

Signs are ubiquitous indoors and outdoors, which are used for way finding, finding shops and businesses, accessing variety of services. But the information of signs is inaccessible to many visually impaired people unless they are represented in a non-visual form such as Braille, tactile graphic, and speech. Automatic reading text from signs in natural images becomes a vital application in visually impaired people assistance. However, finding the text in scene images is a great challenge, because it cannot be assumed that the acquired image contains only characters. Natural scene images usually contain diverse complex text of different size, styles and colors with complex backgrounds. Therefore, this paper proposes a novel method for text extraction from scene images. The algorithm is implemented and evaluated using a set of natural scene images. Accuracy, precision and recall rates of the proposed method are analyzed to determine the success and limitation. Recommendations for improvements are given based on the results.

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