Circular traffic sign recognition empowered by circle detection algorithm

21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS WOS: 000325005300272 Automatic traffic sign detection and recognition is one of the most important components of advanced driver assistance systems. In this paper, a novel method utilizing histograms of oriented gradients based features together with a recently developed and successful circle detection algorithm is proposed for circular traffic sign recognition. In the proposed method, irrelevant backgrounds of traffic signs, whose locations on images are identified within rectangular boundaries, are filtered by detecting their actual circular boundaries. In this way, features representing the traffic signs better can be extracted. The results of the experimental study conducted on a considerably large database demonstrate that the proposed method offers a higher classification performance than the case in which the circle detection is not applied

Benchmarking a network of PCs running parallel applications

We present a benchmarking study that compares the performance of a network of four PCs connected by 100 Mb/s Fast Ethernet running three different system software configurations: TCP/IP on Windows NT, TCP/IP on Linux and a light weight message passing protocol (U-Net Active messages) on Linux. For each configuration, we report results for communication micro-benchmarks and the NAS parallel benchmarks. For the NAS benchmarks, the overall running time using Linux TCP/IP was 12 to 500 percent less than the Windows NT TCP/IP configuration. Likewise, the Linux U-Net based message passing protocol outperformed the Linux TCP/IP version by 5 to over 200 percent. We also show that using Linux U-Net we are able to achieve 125 micro-second latency between two processe