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A visual driver support system was developed to reduce accidents involving motorcyclist. The system used Matlab software as a platform to detect motorcycle image. The detection system was designed to detect still images and moving objects images for different resolutions. A motorcycle was defined as the target object in this case. The results showed that the visual driver support system is able to detect image of motorcycle in still and in moving condition. The percentage of correct detection of motorcycle image is 83.3% and 50% for low and high image resolutions respectively.

Detection of delamination defect in glass fiber reinforced plastics (GFRP) by using ultrasonic testing has been a challenging task in industry. The properties of the constituent materials, fiber orientation and the stacking sequence of laminated composite materials could cause high attenuation of ultrasound signals. Ultrasonic testing is based on the interpretation of the reflected ultrasound signals when a transducer imposes ultrasound waves (pulse) to a material. It is difficult to differentiate if the reflected signal is induced from the defects, fiber content or the intermediate layers of GFRP composites. Most of the time, the drastic attenuation of signals could enshroud the modest changes in the reflected signals from defects. The purpose of this paper is to investigate the influence of fiber orientation, thickness and delamination of GFRP composites on the rise time, pulse duration and attenuation ratio of the reflected ultrasound signal. The rise time, pulse duration and attenuation ratio of Ascan data was observed with respect to different positions of damage (delamination), thickness and stacking sequence of the lamina. It is essential to identify the significant factors that contribute to the abnormal characteristics of the reflected signals in which the defect is identified. Moreover, this paper presents the application of Taguchi method for maximizing the detection of defect in GFRP composites influenced by delamination. The optimum combination of the significant contributing factor for the signal's abnormal characteristics and its effect on damage detection was obtained by using the analysis of signal-to-noise ratio. The finding of this study revealed that delamination is the most influential factor on the attenuation ratio.

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