Abstract
Computer vision is one of the fields of research that can be applied in a various subject. One application of computer vision is the hand gesture recognition system. The hand gesture is one of the ways to interact with computers or machines. In this study, hand gesture recognition was used as a password for electronic key systems. The hand gesture recognition in this study utilized the depth sensor in Microsoft Kinect Xbox 360. Depth sensor captured the hand image and segmented using a threshold. By scanning each pixel, we detected the thumb and the number of other fingers that open. The hand gesture recognition result was used as a password to unlock the electronic key. This system could recognize nine types of hand gesture represent number 1, 2, 3, 4, 5, 6, 7, 8, and 9. The average accuracy of the hand gesture recognition system was 97.78% for one single hand sign and 86.5% as password of three hand signs.
Highlights
IntroductionApplying technology to the door lock system can make the door open only through the authentication process
Security access using conventional keys is at risk of being lost or duplicated
We developed a hand gesture based electronic key based on the depth sensor of Microsoft Kinect
Summary
Applying technology to the door lock system can make the door open only through the authentication process. This authentication process can be in the form of passwords, electronic key, and even biometrics. Hand gesture can be understood by looking at the signals that are delivered and sent to the brain and processed by the brain to mean the meaning of the signal. Several studies have been conducted related to electronic key based on this hand gesture. The hand image and background were separated based on the color similarity with the skin color. This method could distinguish five different sign namely signals A, B, C, D, and E. Data from the accelerometer was processed using the Multi-Layer Perceptron artificial neural network so that the sign could be recognized
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