首页> 外文OA文献 >Study of object detection and reading(license plate detection and reading)
【2h】

Study of object detection and reading(license plate detection and reading)

机译:物体检测与读取研究(车牌检测与读取)

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Object detection means finding the location of the object and recognizing what it is. The techniques used for the object detection are feature matching algorithm, pattern comparison and boundary detection. The feature matching algorithm is used to find the best matching object in the knowledge base and to implement the reconstruction of the object recognized.udOur object detection is to detect the license plate detection of the car. To detect the license plate of a car first pre-process the image. The commonly license plate locating algorithms include line detection method, neural networks method, fuzzy logic vehicle license plate locating method. “Connected component analysis” is very easy technique than these techniques.udIn the pretreatment process we first crop the image. After this we convert the color image to gray level image. After converting into gray level that image is filtered using three different types of filters. They are Average, Median, Weiner filters. After deciding the good filter we will apply the segmentation process using edge detection. After finding the edges we will give the numbers to each connected component and store all the connected components in a matrix called labeling matrix. Extract the required connected component using the labeling matrix and store that in an image. Compare this template with our database using template matching technique.udTemplate matching technique uses the correlation procedure. We will find the correlation coefficient between the two templates. Depending upon the correlation coefficient we will find that how much the two templates are similar to each other.ud
机译:物体检测意味着找到物体的位置并识别它是什么。用于对象检测的技术是特征匹配算法,模式比较和边界检测。特征匹配算法用于在知识库中找到最匹配的对象,并实现对所识别对象的重构。 ud我们的对象检测是检测汽车的车牌检测。要检测汽车的车牌,请先对图像进行预处理。常见的车牌定位算法包括线检测法,神经网络法,模糊逻辑车辆车牌定位法。 “连接组件分析”是比这些技术更简单的技术。 ud在预处理过程中,我们首先裁剪图像。之后,我们将彩色图像转换为灰度图像。转换为灰度后,将使用三种不同类型的滤镜对图像进行滤镜。它们是“平均”,“中位数”,“韦纳”过滤器。在确定好滤波器后,我们将使用边缘检测来应用分割过程。找到边缘后,我们将为每个连接的组件赋予编号,并将所有连接的组件存储在称为标签矩阵的矩阵中。使用标签矩阵提取所需的连接组件并将其存储在图像中。使用模板匹配技术将此模板与我们的数据库进行比较。 udTemplate匹配技术使用相关过程。我们将找到两个模板之间的相关系数。取决于相关系数,我们将发现两个模板彼此相似的程度。 ud

著录项

  • 作者

    Gajula Nanda kishore;

  • 作者单位
  • 年度 2011
  • 总页数
  • 原文格式 PDF
  • 正文语种
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号