在移动应用程序上使用云计算和Google api实现阿拉伯手写识别方法

Nada Shorim, Taraggy M. Ghanim, Ashraf AbdelRaouf
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引用次数: 2

摘要

现在需要云计算应用程序来自动识别阿拉伯手写体,特别是在移动应用程序上实现时,这一点非常重要。这是一种应用程序类型,包含许多具有挑战性的方面。本文首次介绍了一个基于云的移动应用程序,该应用程序将阿拉伯语手写识别用于翻译目的和在谷歌地图上查找位置。为非阿拉伯语使用者提供这样的服务是非常重要的,特别是在访问阿拉伯语国家时。我们的方法是第一个建立一个基于云计算的移动应用程序,提出了一个用于阿拉伯手写文本识别的多阶段混合分类器。作为引入的云计算应用程序的一部分,将Google Maps和Google Translate api应用于识别的文本。该方法的识别部分是为了应对大数据库和高计算复杂度而引入的多阶段分类器。实验结果表明,与同类方法相比,我们的方法具有更好的识别效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementing Arabic Handwritten Recognition Approach using Cloud Computing and Google APIs on a mobile application
Cloud computing application for automatic recognition of Arabic handwritten is needed nowadays and of great importance especially when implemented on a mobile application. It is a type of applications that includes many challenging aspects. This paper introduces for the first time a cloud based mobile app that applies Arabic handwritten recognition for translation purposes and finding locations on Google maps. Proposing such a service for non-Arabic speakers is of great importance especially while visiting Arabic speaking countries. Our approach is the first to build a mobile app based on cloud computing that proposes a multi-phase hybrid classifier for Arabic Handwritten text recognition. Google Maps and Google Translate APIs are applied on the recognized text as part of the introduced cloud computing application. The recognition part of the proposed approach is a multi-stage classifier introduced to cope with big database and high computation complexities. The experiment applied on our approach shows better results of our Arabic handwritten recognition when compared with similar approaches.
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