Journals >Laser & Optoelectronics Progress
ing at the face images in large angle oblique illumination and extremely dark and uneven illumination environment, an illumination compensation method is proposed based on anisotropic Retinex transform. First, according to the statistical characteristics of face image, the direction of the light source is analyzed, and the edge is detected by Prewitt operator. Combined with the geometric characteristics of the face texture, the curvature, slope and symmetry are introduced to achieve the unevenness of the face and illumination, thus distinguishing the false edge of the face. Second, based on the Weickert structure tensor, an improved anisotropic diffusion model is implemented based on different types of edges. The model is combined with Retinex algorithm to realize face image illumination compensation. The experimental results show that the improved anisotropic diffusion method can enhance the image brightness, prominent texture detail, and eliminate most light shadow at the same time enhancing face edge.
.ing at the problem that the conventional lane detection system uses a single-channel forward-looking camera under night scenes, which is susceptible to strong light interference and is prone to false detection and misdetection in complex scenes, we propose a lane detection method based on active infrared filter and around-view imaging. In the imaging stage, four-way vehicle-borne cameras based on active infrared filter are used to collect scene information around the vehicle, and then a look-around image with 360° overlooking effect is obtained based on perspective transformation and image fusion. In the detection phase of lane, a lane detection algorithm is proposed based on agglomerative hierarchical clustering. Firstly, based on the shape features of lane lines, a more pertinent template matching is designed to extract the edge points of the lane line. Then the edge points are clustered by agglomerative hierarchical clustering, and the lane is fitted by the random sample consensus algorithm. Finally, a priori information and Kalman filter are combined to further improve detection accuracy. The results show that the proposed algorithm can effectively eliminate the strong light effects during the detection of lanes and effectively reduce the false detection and missed detection rate to a certain extent.
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