An innovative approach for on-road real-time preceding vehicle detection system is presented in this paper. Vehicle detection is performed by using knowledge based candidate generation followed by appearance based verification. The primary shadow present underneath the vehicle chassis i.e. self shadow is used to generate candidate regions in the image. The use of only self shadow provides improved results and robustness as compared to cast shadows utilized in other approaches.The vehicle class has large intra-class variance due to which a large training dataset with normalized samples is needed for accurate classifier design. It is proposed that the deterministic structure of the contour of vehicles remains same irrespective of its appearance. Hence, structural analysis using the edge based features can be used for classification. It is proposed that a smaller training data-set which is not necessarily normalized is sufficient for good classification results using this analysis. This leads to reduced complexity in system design
This paper reports an automatic instrument developed for characterization of optical waveguides. A specially designed waveguide excitation unit offers a flexible platform for measurement of optical waveguide characteristics like number of propagating modes, mode field intensity distribution, the refractive index profiles, waveguide geometry, attenuation, and dispersion. Further, the availability of attachments like filters, polarizers, chopper, intensity profiler, and CCD camera make the instrument flexible enough for a variety of other experiments also. The instrument is PC controlled and assisted by user friendly menu-driven software. A large number of waveguides have been analyzed using the setup. These results are also presented in the paper.
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