A homogeneous region based methodology for text extraction from natural scene images

Jianjun Chen, N. Takagi
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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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基于均匀区域的自然场景图像文本提取方法
标志在室内和室外无处不在,用于指路,寻找商店和企业,获得各种服务。但是,许多视障人士无法获得标志的信息,除非它们以非视觉形式表示,如盲文、触觉图形和语音。在视障人士辅助中,从自然图像中自动读出文字已成为一项重要的应用。然而,在场景图像中寻找文本是一个巨大的挑战,因为不能假设获取的图像只包含字符。自然场景图像通常包含不同大小、风格和颜色的复杂文本,背景复杂。为此,本文提出了一种新的场景图像文本提取方法。该算法使用一组自然场景图像来实现和评估。分析了该方法的准确率、精密度和召回率,以确定该方法的成功和局限性。根据结果提出改进建议。
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