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One of the latest authentication methods is by discerning human gestures. Previous research has shown that different people can develop distinct gesture behaviours even when executing the same gesture. Hand gesture is one of the most commonly used gestures in both communication and authentication research since it requires less room to perform as compared to other bodily gestures. There are different types of hand gesture and they have been researched by many researchers, but stationary hand gesture has yet to be thoroughly explored. There are a number of disadvantages and flaws in general hand gesture authentication such as reliability, usability, and computational cost. Although stationary hand gesture is not able to solve all these problems, it still provides more benefits and advantages over other hand gesture authentication methods, such as making gesture into a motion flow instead of trivial image capturing, and requires less room to perform, less vision cue needed during performance, and so forth. In this paper, we introduce stationary hand gesture authentication by implementing edit distance on finger pointing direction interval (ED-FPDI) from hand gesture to model behaviour-based authentication system. The accuracy rate of the proposed ED-FPDI shows promising results

Stationary Hand Gesture Authentication Using Edit Distance on Finger Pointing Direction Interval