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基于背景纹理的轿车车标定位方法
引用本文:李映东,吴晓红,卿粼波,何小海.基于背景纹理的轿车车标定位方法[J].计算机系统应用,2020,29(1):190-195.
作者姓名:李映东  吴晓红  卿粼波  何小海
作者单位:四川大学 电子信息学院, 成都 610065;四川大学 电子信息学院, 成都 610065;四川大学 电子信息学院, 成都 610065;四川大学 电子信息学院, 成都 610065
基金项目:国家自然科学基金(61871278);四川省科技计划(2018HH0143);四川省教育厅科研项目(18ZB0355);成都市产业集群协同创新项目(2016-XT00-00015-GX)
摘    要:车标定位是车标识别系统的关键技术之一,但是由于车标背景的散热片纹理不一、种类繁多,给车标定位造成了困难,故提出了一种基于背景纹理的轿车车标定位方法.该方法首先根据先验知识对车标进行粗定位,依据其在水平投影与垂直投影上的特征将车标背景分为三大类,然后运用Sobel算子分别对不同类别的散热片背景进行消融;为了更好的去除散热片背景对定位车标的影响,引入了一种邻间二值化方法,同时结合基于投影的去噪方法对噪点进行进一步处理,从而实现车标的精确定位.这种方法适用于不同类型的车标背景条件下的车标定位.实验通过对1000张图片进行车标定位,比较已有算法有更高的准确率和适用性,总体定位准确率可以达到97.10%.

关 键 词:车标定位  背景分类  邻间二值化  投影去噪
收稿时间:2019/5/30 0:00:00
修稿时间:2019/6/28 0:00:00

Location Method of Vehicle Logo Based on Background Texture
LI Ying-Dong,WU Xiao-Hong,QING Lin-Bo and HE Xiao-Hai.Location Method of Vehicle Logo Based on Background Texture[J].Computer Systems& Applications,2020,29(1):190-195.
Authors:LI Ying-Dong  WU Xiao-Hong  QING Lin-Bo and HE Xiao-Hai
Affiliation:College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China,College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China,College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China and College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China
Abstract:Vehicle logo location is one of the key technologies of vehicle logo recognition system. However, because of the different texture and variety of radiators in the background, it is difficult to locate the vehicle logo. Therefore, a vehicle logo location method based on background texture is proposed. Firstly, the method locates the vehicle logo roughly according to prior knowledge, then divides the background of the vehicle logo into three categories according to its characteristics on horizontal and vertical projections, and then uses Sobel operator to ablate the background of different types of radiators. In order to better remove the influence of radiator background on the location of the vehicle logo, a neighborhood binarization method is introduced, which combines projection-based method. The denoising method further deals with the noise points, so as to realize the accurate positioning of the vehicle logo. This method is suitable for different types of vehicle logo background conditions. The experiment results show that the proposed algorithm has higher accuracy and applicability by positioning 1000 images, and the overall positioning accuracy can reach 97.10%.
Keywords:vehicle positioning|background classification|neighborhood binarization|projection denoising
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