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首页> 外文期刊>Indian Journal of Science and Technology >Camera based Text to Speech Conversion, Obstacle and Currency Detection for Blind Persons
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Camera based Text to Speech Conversion, Obstacle and Currency Detection for Blind Persons

机译:基于相机的盲人文本到语音转换,障碍和货币检测

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Background/Objectives: The main object of this paper is to present an innovated system that can help the blind for handling currency. Methods/Statistical Analysis: Many image processing techniques have been used to scan the currency, remove the noise, mark the region of interest and convert the image into text and then to sound which can be heard by the blind. The entire system is implemented by using Raspberry Pi Micro controller based system. In the proto type model an IPR sensor is used instead of camera for sensing the object. Findings: In this paper a novel method has been presented using which one can recognize the object, mark the interesting region within the object, scan the text and convert the scanned text into binary characters through optical recognition. A second method has been presented using which the noise present in the scanned image is eliminated before characters are recognized. A third method that can be used to convert the recognised characters into e-speech through pattern matching has also be presented. Applications: An embedded system has been developed based on ARM technology which helps the blind persons to read the currency notes. All the methods presented in this paper have been implemented within an embedded application. The embedded board has been tested with different currency notes and the speech in English has been generated that identify the value of the currency. Further work can be done to generate the speech in different other both National and International Languages.
机译:背景/目的:本文的主要目的是提出一个创新的系统,可以帮助盲人处理货币。方法/统计分析:已使用许多图像处理技术来扫描货币,消除噪声,标记感兴趣的区域并将图像转换为文本,然后转换为盲人可以听到的声音。整个系统是通过使用基于Raspberry Pi Micro控制器的系统来实现的。在原型模型中,使用IPR传感器代替摄像机来感测物体。发现:本文提出了一种新颖的方法,利用该方法可以识别物体,标记物体内的有趣区域,扫描文本并将扫描后的文本通过光学识别转换为二进制字符。已经提出了第二种方法,利用该方法在识别字符之前消除了扫描图像中存在的噪声。还提出了可用于通过模式匹配将识别的字符转换为电子语音的第三种方法。应用:基于ARM技术的嵌入式系统已经开发出来,可以帮助盲人阅读纸币。本文介绍的所有方法均已在嵌入式应用程序中实现。嵌入式板已通过不同的纸币进行了测试,并且生成了英语的语音来标识货币的价值。可以做进一步的工作来生成使用其他本国语言和国际语言的语音。

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