The Recognition Of Semaphore Letter Code Using Haar Wavelet And Euclidean Function

L. Putra, Linggo Sumarno, Vincentius Abdi Gunawan
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引用次数: 2

Abstract

Semaphore are one way of communicating over long distances using the semaphore flags. In Indonesia semaphore is used in scout activities as a method to send information in the form of a sentence containing the message. Sending the semaphore letter code tends to be difficult. Based on the need to semaphore learning, this research proposes an algorithm with image processing as a way to correct the movement of the semaphore letter code based on the image obtained by using the webcam. Digital image processing, Wavelet feature extraction, and Euclidean distance function are applied in this study to determine the best recognition rate of variation decimation and distance variation to sending semaphore letter code using the webcam. This study resulted in the best recognition rate of 95.4% in the 1st decimation, recognition rate reached 94.6% in decimation 2, and recognition rate reached 94.2% in decimation 3. The result of the introduction of the semaphore letter code is on the introduction of movement as far as 3 to 5 meters.
基于Haar小波和欧氏函数的信号量字母码识别
信号量是使用信号量标志进行长距离通信的一种方式。在印度尼西亚,信号量被用于侦察活动,作为一种以包含信息的句子形式发送信息的方法。发送信号量字母代码往往是困难的。基于信号量学习的需要,本研究提出了一种基于图像处理的算法,基于使用摄像头获取的图像对信号量字母码的运动进行校正。本研究采用数字图像处理、小波特征提取和欧氏距离函数,确定了网络摄像头发送信号量字母码的变异抽取和距离变异的最佳识别率。本研究的最佳识别率为第一次抽取95.4%,第二次抽取识别率为94.6%,第三次抽取识别率为94.2%。引入信号量字母码的结果是对引入运动最远3至5米。
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