Abstract: Bit dependency of image compression algorithms introduce error extension effects in transmission of compressed images and considerably reduce the received image quality. Channel coding provides protection against these errors but at the cost of increased bandwidth. Asymmetric modulation methods like QAM and QPSK provide alternative means of equal error protection to all the coded bits without increasing the bandwidth. This paper examines the suitability of Hierarchical QAM (HQAM) where non-uniform signal constellation is used to provide different degrees of protection to the significant and non-significant bits in the compressed image data at lower channel Signal to Noise Ratio (SNR) and compares it with that of QAM. The performance of HQAM is evaluated using gray test image for different values of the modulation parameter.

Abstract: The demand for security in wireless communication channels is rapidly growing. In this exertion a proposed encryption unit which adopts the AES (Advanced Encryption Standard) as the encryption algorithm is presented. In previous work a customized version of the “AES” block cipher to suit proprietary data encryption applications is introduced [1]. In this paper, a hardware implementation of the algorithm, using Field Programmable Gate Arrays (FPGA) is presented. Furthermore, the structure of Encryption unit, the implemented micro-architecture, the simulation, and implementation results will be discussed. In addition, the detailed description of the various micro-architecture modules is included.

Keywords: Advanced Encryption Standard (AES), Field programmable gate arrays (FPGA), Very high speed integrated circuit Hardware Description Language (VHDL), Micro-Architecture, Encryption, and Algorithm.

Abstract: This article proposes a method of parameters estimation by analyzing a video in which a traffic accident is recorded.  At the scene of an accident, vehicle properties such as position and velocity are important for the investigators, but they are not easy to be obtained for the difficulty of telling the state of a surveillance camera. Here a method is presented by taking good advantages of road traffic markings and the remote image from Google earth, with which the inverse projective transformed image from surveillance traffic video is matched in order to gain the vehicle properties. As a result, compared with an official report, parameters of a traffic accident mentioned are accurately estimated by image and video processing. And error analysis has also been concerned. At the conclusion, necessary requirements are discussed for common applications.

Keywords: Video processing, Traffic accident, Pavement Markings, Inverse Projective transformation