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Indian Sign Language Recognition using AlexNet

机译:使用AlexNet的印度手语识别

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摘要

Sign language is the language which people with hearing problems used to communicate. The problem will be more complicated if the listener is does not understand the sign language. Here in this project we made use of image based hand gesture recognition techniques for identifying the sign language. The input sequence of images are captured with a digital camera. It is then passed through a sequence of preprocessing steps for the removal of background noise. The image is segmented based on the skin colour and is later on edge segmented to obtain the exact shape of the detected skin pixel. Canny edge detector is used for this purpose. The recognition of hand or body with surroundings is done by comparing the brightness information in HSI colour model. The colour thresholded image is then given to the AlexNet and the gesture signaled is identified in to a particular category and the label is extracted.
机译:手语是用来沟通的听力问题的语言。 如果侦听器不了解手语,问题将更加复杂。 在此项目中,我们利用了基于图像的手势识别技术来识别手语。 用数码相机捕获图像的输入序列。 然后通过一系列预处理步骤来删除背景噪声。 基于肤色分割图像,并且稍后在边缘分段以获得检测到的皮肤像素的精确形状。 罐头边缘检测器用于此目的。 通过比较HSI颜色模型中的亮度信息来完成对周围环境的手或身体的识别。 然后将颜色阈值的图像置于亚历尼管,并且识别给语势信号被识别到特定类别,并提取标签。

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