Object recognition system design in regions of interest based on AdaBoost algorithm

Automotive technology has been recently challenged with the issue of ensuring and improving road safety. Several academic institutions and automobile manufacturers are making efforts to develop technology for automotive safety. This study proposes an object recognition system based on the adaptive boosting algorithm that integrates a laser range finder and a camera. The laser range finder is used to measure the distances of objects in front of the vehicle and then, their central position and length can be calculated. The camera is used to capture sequences of images. The positions of objects in the image are extracted using the corner detection method and optical flow. Coordinate transformation based on curve fitting is used to integrate the distance information from the laser range finder with the information contained in the image. The adaptive boosting algorithm is adopted to recognize objects in front of the vehicle as pedestrians or cars. Finally, the system will trigger an alarm once an obstacle is detected in a region of interest. The experimental results show that the accuracy rate is improved after the combination of the sensors.