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Mobile Application Based Translation of Sign Language to Text Description in Kannada Language

机译:基于移动应用程序的手语翻译在Kannada语言中的手语

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Sign language is a main mode of communication for vocally disabled. This language use set of representation which is finger sign, expression or mixture of both to express their information among others. This system presents a novel approach for mobile application based translation of sign action analysis, recognition and generating a text description in Kannada language. Where it uses two important steps training and testing. In training set of 50 different domains of video samples are collected, each domain contains 5 samples and assign a class of words to each video sample and it will be store in database. Where in testing test sample under goes preprocessing using median filter, canny operator for edge detection, HOG for feature extraction. SVM takes input as a HOG features and predict the class label based on trained SVM model. Finally the text description will be generated in Kannada language. The average computation time is minimum and with acceptable recognition rate and validate the performance efficiency over the conventional model.
机译:手语是障碍障碍的主要沟通模式。这种语言使用表现形式,这两者都是指示他们在其它信息等中表达他们的信息的手指标志,表达或混合。该系统提出了一种基于kannada语言的签名行动分析,识别和生成文本描述的移动应用程序的新颖方法。它使用了两个重要的步骤培训和测试。在收集50个不同域的训练集中,每个域包含5个样本并将一类单词分配给每个视频样本,它将在数据库中存储。在测试测试样品的位置,使用中值过滤器进行预处理,罐头操作员进行边缘检测,为特征提取的HOG。 SVM将输入作为HOG功能,并根据训练的SVM模型预测类标签。最后,将在Kannada语言中生成文本描述。平均计算时间最小,并且具有可接受的识别率并通过传统模型验证性能效率。

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