基于背景纹理的轿车车标定位方法
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

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)


Location Method of Vehicle Logo Based on Background Texture
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    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%.

    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%.

    参考文献
    相似文献
    引证文献
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.计算机系统应用,2020,29(1):190-195

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2019-05-30
  • 最后修改日期:2019-06-28
  • 录用日期:
  • 在线发布日期: 2019-12-30
  • 出版日期: 2020-01-15
文章二维码
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京海淀区中关村南四街4号 中科院软件园区 7号楼305房间,邮政编码:100190
电话:010-62661041 传真: Email:csa (a) iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号