The Lane Mark Identifying and Tracking in Intense Illumination

In order to enhance image contrast and ensure accurate identifying and tracking in intense illumination case, this chapter uses the algorithm of histogram cone-shaped, which can enhance image contrast effectively. With the algorithm of histogram cone-shaped, the scope of the gray value increases obviously. And the chapter introduces a first-order differential operator two-direction Prewitt operator to enhance the edge for image; the enhance effect is favorable, and the compute time is short. Then the algorithm of 2-D gray histogram is used to segment image. The chapter uses Hough transformation to identify the lane mark’s two edges and account its intercept and slope and then draws the midline as the last identifying result. In order to reduce the count time, the chapter uses the algorithm of area of interesting to track the lane mark. The experiment results show that the lane mark can be tracked dependably in intense illumination and the algorithms are of real time; moreover, when the tracking algorithm is a failure, the system can also recover in time and lock the tracking target accurately again.