Video surveillance systems play an important role in the crime scene investigation, and the digital surveillance system always requires the superimposed video data being subjected to a data compression processing. The purpose of this paper is to study the use of inpainting techniques to remove the characters and inpaint the target region. We give the efficient framework including getting Character Superimposition mask, superimposition movement and inpainting the blanks. The character region is located with the manual ROI selection and varying text extractor, such as the time. The superimposed characters usually have distinguished colors from the original background, so the edges are easily detected. We use the canny operator the get the edge image. The missing information which is effect the structure of the original image is reconstructed using a structure propagating algorithm. The experiment was done with C/C++ in the vs2010 KDE. The framework of this paper showed is powerful to recreate the character superimposition region and helpful to the crime scene investigation.
Advances in digital video compression and IP communication technologies raised new issues and challenges concerning the integrity and authenticity of surveillance videos. It is so important that the system should ensure that once recorded, the video cannot be altered; ensuring the audit trail is intact for evidential purposes. This paper gives an overview of passive techniques of Digital Video Forensics which are based on intrinsic fingerprints inherent in digital surveillance videos. In this paper, we performed a thorough research of literatures relevant to video manipulation detection methods which accomplish blind authentications without referring to any auxiliary information. We presents review of various existing methods in literature, and much more work is needed to be done in this field of video forensics based on video data analysis and observation of the surveillance systems.
Conventional optical video surveillance systems usually just record what they view, but they can’t make sense of what they are viewing. With lots of useless video information stored and transmitted, waste of memory space and increasing the bandwidth are produced every day. In order to reduce the overall cost of the system, and improve the application value of the monitoring system, we use the Kinect sensor with CMOS infrared sensor, as a supplement to the traditional video surveillance system, to establish the natural user interface system for indoor surveillance. In this paper, the architecture of the natural user interface system, complex background monitoring object separation, user behavior analysis algorithms are discussed. By the analysis of the monitoring object, instead of the command language grammar, when the monitored object need instant help, the system with the natural user interface sends help information. We introduce the method of combining the new system and traditional monitoring system. In conclusion, theoretical analysis and experimental results in this paper show that the proposed system is reasonable and efficient. It can satisfy the system requirements of non-contact, online, real time, higher precision and rapid speed to control the state of affairs at the scene.
In this paper we develop a novel practical application, which give scalable services to the end users when abnormal actives are happening. Architecture of the application has been presented consisting of network infrared cameras and a communication module. In this intelligent surveillance system we use Kinect sensors as the input cameras. Kinect is an infrared laser camera which its user can access the raw infrared sensor stream. We install several Kinect sensors in one room to track the human skeletons. Each sensor returns the body positions with 15 coordinates in its own coordinate system. We use calibration algorithms to calibrate all the body positions points into one unified coordinate system. With the body positions points, we can infer the surveillance context. Furthermore, the messages from the metadata index matrix will be sent to mobile phone through communication module. User will instantly be aware of an abnormal case happened in the room without having to check the website. In conclusion, theoretical analysis and experimental results in this paper show that the proposed system is reasonable and efficient. And the application method introduced in this paper is not only to discourage the criminals and assist police in the apprehension of suspects, but also can enabled the end-users monitor the indoor environments anywhere and anytime by their phones.