Handwritten English Character and Digit Recognition Using Kinect
Date Issued
2014
Date
2014
Author(s)
Wang, Hao-Yu
Abstract
Human-computer interaction (HCI) has been a popular research field recently. Hand gesture recognition is an important part of HCI that provides a natural way of communication. Handwritten recognition is a part of hand gesture recognition that provides an alternative method to input characters. In this thesis, we propose a handwritten recognition system to input English characters and digits without using traditional input devices such as keyboards and mice.
Accuracy and real time processing are highly desired in the handwritten digit and character recognition of HCI. In order to improve the accuracy, we suggest a new feature extracting algorithm which contains the temporal and spatial information of hand writing paths. Furthermore, we use support vector machines and random forests to carry out feature classification. Experimental results show that the proposed method has a very high accuracy in the handwritten digit and character recognition in real time.
Accuracy and real time processing are highly desired in the handwritten digit and character recognition of HCI. In order to improve the accuracy, we suggest a new feature extracting algorithm which contains the temporal and spatial information of hand writing paths. Furthermore, we use support vector machines and random forests to carry out feature classification. Experimental results show that the proposed method has a very high accuracy in the handwritten digit and character recognition in real time.
Subjects
模式識別
手寫數字辨識
手寫英文字母辨識
動態手勢辨識
Type
thesis
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