Abstract
Video surveillance system is widely adopted in order to secure life. This paper presents embedded home surveillance systems to detect intruder in home environment. Proposed system works on embedded Linux board which is equipped with an ordinary web camera. At software level, it uses Open Computer Vision library to detect intruder in two different steps, Histogram of Oriented Gradient and Haar Like Features in association with Support Vector Machine. Moreover, it compares reference histogram to histogram of current image frame by using correlation methods and interpolates change of contents or light intensity in order to optimize the system in terms of false alarm minimization. Along with the Video server, Internet of Things application architecture has been adopted that provides remote monitoring. Alarm service, follows service oriented architecture; execute a set of predefined tasks such as alarming bell, turn on or off switches. This system provides a way to validate each camera module, able to detect device fault, examine image quality and image content changes. The system software provides an architectural solution for intelligent home surveillance system by incorporating Computer Vision and Digital Image Processing algorithms.
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