Ground-image plane mapping for lane marks detection

Autonomous vehicles are equipped with optical sensors and micro-processing units to perform intelligent visual analysis of its surroundings. Due to the high speed of moving vehicle, the captured information has to be processed in a short duration to avoid possible collision. In this paper, a ground-image plane mapping technique is proposed to quickly locate detected object if the object´s position is known in the real world. A three dimensional (3D) world coordinate is mathematically derived to an image plane using pinhole camera model. Several 3D perspective parameters such as vehicle´s steering angle and its velocity, sensor´s height and tilting angle are encompassed in the ground plane measurement. The optical sensor´s intrinsic parameters such as focal length, principal point, pixel´s height and width are also inserted for the mathematical model derivation. The importance of this ground to image plane mapping enables a rapid search of an object in a moving scene to achieve fast object identification during sensor acquisition. Experimental results have been carried on the application of lane marks detection with 93.82% correct mapping, using approximately 20% less processing time.