【摘要】 针对实际拍摄场景中的复杂光照条件以及不同车牌颜色对车牌定位造成的影响,提出了一种基于高斯差分图像的AdaBoost车牌检测算法.该算法首先对原始灰度图像进行高斯差分,得到其对应的高斯差分图像,然后利用基于DoG图像的DoG+AdaBoost分类器与基于灰度图像的G ray+AdaBoost分类器构成二级车牌检测器进行车牌检测,最后根据车牌中的车牌号码信息对车牌检测结果进行验证,得到最终的车牌定位结果.该算法利用高斯差分方法,很好地抑制了复杂光照和不同车牌颜色对车牌检测造成的影响,具有较快的定位速度和很高的检出率.实验表明,该算法能获得很好的车牌定位效果,具有较高的实用价值.更多还原

【Abstract】 While focusing on the effect of complex illumination conditions in an actual shooting scene and different colors of a license plate in various locations,a license plate detection method was presented based on the DoG+AdaBoost algorithm.First,by differential Gaussian processing,the DoG image was obtained from the gray-scale image,and then a 2-stage detector formed by the DoG+AdaBoost classifier and Gray+AdaBoost classifier was used to detect the license plate.Finally,the registration number information was used to verify the license plate and to produce the final result.The algorithm greatly reduced the effect of complex illumination conditions and different colors of the license plate in various locations with a fast processing time and high detection rate.The algorithm performed well in the experiment and possesses high practical value.更多还原