As the number of application of images on the Internet increases, how to store and transmit these images becomes a big challenge. JPEG as the most widely used image compression format on the Internet is often applied to pictures compression. However, just using JPEG alone to compress images is not enough now. In hence, some methods use improved entropy coding to further recompress JPEG images losslessly or process the images on DCT domain for lossy recompression. These methods are useful and work for various images. But there is no special design for fixed surveillance applications. Depending on the feature of images generated by a same fixed surveillance camera, a JPEG image lossless recompression method based on CABAC pre-coding, residual coefficients between JPEG image group and simplified context prediction is proposed by us. With a little reduction of decoding time as well as little increase of encoding time, average 27% bits saving can be achieved in the experiment.
KEYWORDS: Visualization, Detection and tracking algorithms, Genetic algorithms, Imaging systems, Visual process modeling, Information visualization, RGB color model, Parallel computing, Video acceleration, Video
Template matching for image sequences captured by mobile camera is widely applied in machine vision, RTLS (Real Time Location System), ADAS (Advanced Driver Assistant Systems), ITS (Intelligent Transportation System) and video surveillance system. Nowadays, the target tracking algorithms are mainly divided into two categories: generative model method and discriminative model method. Currently, discriminative model method is popular. This method mainly adopts image feature combined with machine learning to achieve template matching. Such algorithms require adequate image samples and tedious calculations, so there are many difficulties in the application of on-board systems such as ADAS and ITS. In this paper, we present a method based on visual feature information and structure information which can improve the accuracy of template matching effectively and proposed cuda architecture based parallel acceleration algorithm. Compared with previous method, the proposed method can achieve template matching robustly while maintaining a short operation time, so that it can be easily ported to the vehicle-mounted system.
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