基于人工神经网络的手势识别

K.V Eshitha, Soniya Jose
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引用次数: 4

摘要

手势是现实世界中人机交流最简单、最具表现力的方式之一。在我们的日常生活中,我们使用各种手势来表示我们的意图。手势和手势是人类最重要的非语言交流方式。近年来,基于机器界面的手势识别技术有了很大的发展。利用人工神经网络,开发了一种用于垫子实验室手势识别的系统。这里收集了一个包含各种手势的数据集,并通过基于颜色的分割和各种形态学操作从输入图像中分割手势。这里的特征提取是基于梯度直方图方法。分割后的手势分为左手手势和右手手势,并附有标签。这将传递给神经网络进行训练,train-rp是用于训练手势的函数。在测试过程中,将人脸视频输入到系统中,系统将识别帧中相应的输出并进行预测
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hand Gesture Recognition Using Artificial Neural Network
Gesture is one of the most easy and expressive ways of communications between human and computer in a real world. In our day to day life we use various gestures to represent our intention. Hand and face gesture are most important methods for nonverbal communication for human beings. Development in hand gesture recognition using machine interface has got great improvements in recent years. A system is developed for hand gesture recognition in mat lab by using an artificial neural network. Here a dataset is collected with various gestures and through color based segmentation and various morphological operations gestures are segmented from input image. Here feature extraction takes place on the basis of Histogram of Gradient method. After segmentation classifies the gestures into left hand and right hand gestures along with labels. This will passes to the neural network for training and train-rp is the function used for training the gestures. And during the testing face video is given to the system and the system will recognize the corresponding output in the frame and predict it
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