Nowadays, from home monitoring to large airport security, a lot of digital video surveillance systems have been used. Digital surveillance system usually requires streaming video processing abilities. As an advanced video coding method, H.264 is introduced to reduce the large video data dramatically (usually by 70X or more). However, computational overhead occurs when coding and decoding H.264 video. In this paper, a System-on-a-Chip (SoC) based hardware acceleration solution for video codec is proposed, which can also be used for other software applications. The characteristics of the video codec are analyzed by using the profiling tool. The Hadamard function, which is the bottleneck of H.264, is identified not only by execution time but also another two attributes, such as cycle per loop and loop round. The Co-processor approach is applied to accelerate the Hadamard function by transforming it to hardware. Performance improvement, resource costs and energy consumption are compared and analyzed. Experimental results indicate that 76.5% energy deduction and 8.09X speedup can be reached after balancing these three key factors.

No abstract

Nowadays, digital camera based remote controllers are widely used in people’s daily lives. It is known that the edge detection process plays an essential role in remote controlled applications. In this paper, a system verification platform of hardware optimization based on the edge detection is proposed. The Field-Programmable Gate Array (FPGA) validation is an important step in the Integrated Circuit (IC) design workflow. The Sobel edge detection algorithm is chosen and optimized through the FPGA verification platform. Hardware optimization techniques are used to create a high performance, low cost design. The Sobel edge detection operator is designed and mounted through the system Advanced High-performance Bus (AHB). Different FPGA boards are used for evaluation purposes. It is proved that with the proposed hardware optimization method, the hardware design of the Sobel edge detection operator can save 6% of on-chip resources for the Sobel core calculation and 42% for the whole frame calculation

No abstract

No abstract