凸印双面印地文及德文文盲文文件的两阶段盲文字符分割方法

Shreekanth T, V. Udayashankara
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引用次数: 2

摘要

为了保存盲文文件,使其在未来能够为广大视障人士所使用,也为了实现视障人士与健全人之间的双向交流,光学盲文字符识别系统(OBR)是非常必要的。双面盲文文档的识别和转录是一项具有挑战性的任务。这个困难是由于在点间盲文文档中,正面的点(正反)与背面的点(正反)重叠。在这种情况下,通常的模板匹配方法来区分矩形和横向点是无效的。本文提出了一种新的双面盲文点识别系统,该系统采用两阶段高效自适应技术,利用投影轮廓法区分点间盲文的正反点。在本文中,我们提出了(i)用于盲文线分割的水平投影轮廓,(ii)用于盲文词分割的垂直投影轮廓,以及(iii)用于盲文字符分割的水平和垂直投影轮廓以及距离阈值的集成。我们在一个大型数据集上展示了这种分割技术的有效性,该数据集由754个来自不同图像分辨率和不同单词模式的印地语Devanagari盲文文档的单词组成。识别率达到96.9%。
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A two stage Braille Character segmentation approach for embossed double sided Hindi Devanagari Braille documents
The Optical Braille Character Recognition (OBR) system is in significant need in order to preserve the Braille documents to make them available in future for the large section of visually impaired people and also to make the bi-directional communication between the sighted people and the visually impaired people feasible. The recognition and transcribing the double sided Braille document into its corresponding natural text is a challenging task. This difficulty is due to the overlapping of the front side dots (Recto) with that of the back side dots (Verso) in the Inter-point Braille document. In such cases, the usual method of template matching to distinguish recto and verso dots is not efficient. In this paper a new system for double sided Braille dot recognition is proposed, which employs a two-stage highly efficient and an adaptive technique to differentiate the recto and verso dots from an inter-point Braille using the projection profile method. In this paper we present (i) a horizontal projection profile for Braille line segmentation, (ii) vertical projection profile for Braille word segmentation and (iii) Integration of horizontal and vertical projection profiles along with distance thresholding for Braille character segmentation. We demonstrate the effectiveness of this segmentation technique on a large dataset consisting of 754 words from Hindi Devanagari Braille documents with varying image resolution and with different word patterns. A recognition rate of 96.9% has been achieved.
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