Design and Implementation of Human Detection Feature on Surveillance Embedded IP Camera

Abstract

There are many theft cases which happen because there is no tool used as a guard. Based on the situation mentioned, the house owner tends to use a surveillance camera to guard their properties, especially an important area such as house rooms. However, in general, the traditional surveillance camera is a passive device which has no notification feature to inform the house owner. Indeed, it also has no ability to recognize a human existence. So that, the object detection related to the human and also the notification corresponds a criminal action which is going to be acted by the suspected human is really needed. According to the object detection as the human being, there is an image processing needed to treat the picture which is captured by the surveillance camera. There are many ways to improve the object detection performance of the surveillance camera. One of them is by making a captured image sample which is caught by the surveillance camera. Firstly, the human is a moving object. So that, it is necessary to select the method which is related to the moving object detection to make a sampled image. One of the methods which can be applied is the Background Subtraction. When the moving target is known and is sampled, then the next step is by separating the human by classifying it from the object. In this study, human detection is generated by using Face Detection for the first mechanism and for the second mechanism is Head and Shoulders Detection. Both mechanisms are formed in master/slave. Thus, if the master function which is the Face Detection cannot recognize the object as a human, then the Head and Shoulders detection is going to be shown. The inability of master function for detection happens because of less illumination, or an obstacle such as the human face appears in the opposite direction from the lens of the camera. To minimize the detection failure, the night vision feature is also presented in this study for the surveillance camera prototyping. The human object detection by using the Head and Shoulders method as slave feature is still established for minimizing the failure probability. The proposed system works properly, especially when the system uses the combination of Face Detection and also Head and Shoulders method. The usage of night vision feature also improves the accuracy for detecting the object moves more than 80% in several variations of illumination.