• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.164-170
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• 2013

The latest vehicle yields a superior safety and reduction of driving burden by monitoring the driving state of vehicle and its environment with various sensors. To detect other vehicles and objects of the rear left and right-side blind spot area of driver, provide the information about a existence of objects inside the blind spot, and give a signal to avoid collision, this study proposes the intelligent outside rear-view mirror system. This study proposes SILS system with PreScan and Matlab/Simulink to verify practical applicability of developed BSDS. PreScan yields realistic driving environments and road conditions and vehicle model dynamics and collision warning is controlled by Matlab/Simulink.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.233-241
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• 2014

This paper contributes to development of a new method for detecting rear-side vehicles and estimating the positions for blind spot region or providing the lane change information by using vision systems. Because the real image acquired during car driving has a lot of information including the target vehicle and background image as well as the noises such as lighting and shading, it is hard to extract only the target vehicle against the background image with satisfied robustness. In this paper, the target vehicle has been detected by repetitive image processing such as sobel and morphological operations and a Kalman filter has been also designed to cancel the background image and prevent the misreading of the target image. The proposed method can get faster image processing and more robustness rather than the previous researches. Various experiments were performed on the highway driving situations to evaluate the performance of the proposed algorithm.