基于散热器栅格背景精确分类的车标定位方法

发布时间：2018-05-02 18:11

  本文选题：车标定位 + 散热器栅格精确分类　； 参考：《计算机工程与应用》2017年02期

【摘要】：由于车标的背景散热器栅格形状大小不一、颜色不定、背景多样,因此导致了车标定位的困难,故精确分类散热器栅格是准确定位车标的基础。提出了一种基于散热器栅格背景精确分类的车标定位方法,首先依照车牌与车标空间位置关系确定车标粗定位,然后依据栅格纹理特征,利用霍夫变换和灰度值的梯度变化确定散热器栅格背景的类别,进而通过不同算子分别对不同种类栅格背景进行背景消融;为了保证多种光照条件下的准确定位,引入离散度,并将其与大津法进行融合,形成一种适用于车标定位的自适应二值化方法,同时结合形态学对栅格背景进一步处理,得到准确的车标定位。这种方法适用于在不同光照强度和不同类型的车标背景条件下,对车标进行定位。对10类车标、30类散热器栅格共1 200张图像进行车标定位,实验结果显示,图像总体的车标定位准确率可以达到97.67%。
[Abstract]:Because the background radiator grid is different in shape, color and background, it is difficult to locate the vehicle logo, so the accurate classification of radiator grid is the basis of accurately locating vehicle logo. In this paper, a method of vehicle mark location based on radiator grid background classification is proposed. Firstly, the rough location of vehicle mark is determined according to the relationship between license plate and vehicle logo, and then based on the texture feature of grid. The background of radiator grid background is determined by using Hough transform and gradient change of gray value, and the background of different grid background is ablated by different operators. In order to ensure accurate location under various illumination conditions, the dispersion degree is introduced. An adaptive binarization method is formed by combining it with the Otsu method. At the same time, the raster background is further processed in combination with morphology, and an accurate vehicle mark location is obtained. This method can be used to locate vehicle signs under different illumination intensity and different background conditions. A total of 1,200 images of 10 kinds of vehicle marks and 30 kinds of radiator grids were used to locate the vehicle marks. The experimental results show that the accuracy of the overall image can reach 97.67%.
【作者单位】： 中山大学工学院智能交通研究中心;广东省智能交通系统重点实验室;视频图像智能分析与应用技术公安部重点实验室;
【基金】：国家科技支撑计划(No.2014BAG01B04)
【分类号】：U495;TP391.41
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本文编号：1834954