Enhancement of bank security system plays an important role at the present time due to increasing attempts to expose it to many infringements by criminals. This paper proposes a hybrid technique of amplitude and duration to recognize its blink gestures to increase the accuracy of the human security system’s interaction for intelligent bank security, as this hybrid technique implemented analyzing of face, facial landmark detection, and the duration of the eye aspect ratio (EAR) for blink processes. The proposed hybrid technique is evaluated by experimenting a number of blink gesture with two eyes obtained from web camera and the results shows better and more effective analysis and provide high security bank system.

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This paper proposes an effective method for optimizing extraction large class smell using enhanced class normalization rules in order to ease maintenance and improve the quality of software by creating new classes with strongly and similarity attributes and shared behavior.