Face recognition play a vital role in variety of applications from biometrics, surveillance, security, identification to the authentication. In this paper we design and implement a smart security system for restricted area where access is limited to people whose faces are available in the training database. First we are going to detect the face by detecting the human motion. Then face recognition is performed to determine the authority of the person to enter the sensitive area. At the same time, we track the coordinate of detected motion. Failing to recognize the face finally passes the estimated coordinate to anesthetic gun for targeting the intruder automatically. Experimental results demonstrate the effectiveness of proposed security system in order to restrict the unauthorized access and enhanced reliability by use of face recognition.
In the area of home security and protection, visionbased home automation systems (HAS) play a significant role. In this paper, we present the design and implementation of a smart HAS with incorporated intrusion detection to minimize damages caused by burglary. In addition, the proposed HAS integrates a web server to home appliances in order to remotely access and control their status. Intrusion detection, on the other hand, uses Histogram of Oriented Gradients (HOG) feature descriptors and a Support Vector Machine (SVM) classifier for accurate human detection by smartly rejecting false alarms arising from pets. This system comprised of a simple architecture and requires no human intervention. It allows for prompt accessibility, efficient usage of electricity and provides user convenience.
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