摘要
通过融合颜色和边缘特征并进行目标真实性验证研究车牌的定位,提出了融合颜色特征与灰度边缘特征的车牌定位算法,解决了复杂环境下车牌定位困难的问题。车牌具有固定的颜色搭配和丰富的字符边缘,融合二者的定位算法可提取出所有侯选目标。利用车牌伴生与互补特性进行目标真实性验证,实现带反馈的定位,提高了定位准确度,适用于复杂环境下目标数量、类型不确定的车牌目标检测。对复杂环境下获取的981幅彩色图像进行实验,实验结果表明,车牌目标定位准确率超过了99%,验证了算法的有效性。
A location method combining of the fusion for color and edge features with the object authenticity confirmation is presented to solve the problem of Vehicle License Plate （VLP） location under complex environments. The algorithm fused by color features and edge features can extract all possible objects because the vehicle license plate is charaterized by its fixed color assortments and rich charater edges. Then, the object authenticity confirmation by virtue of the features of concomitance and complement is used to realize a feedback location to obtain the multi-object or multi-type object locations under complex environments. An experiment is undertaken with 981 actual RGB color images from various complex environments, and the experimental results show that the object location accuracy is over 99 percent,which proves the proposed object location method is effective and practical.
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2009年第4期886-894,共9页
Optics and Precision Engineering
基金
国家自然科学基金资助项目(No.60541001)
全国优秀博士学位论文作者专项基金资助项目(No.200443)
“泰山学者”建设工程专项经费资助项目
山东省高校优秀青年教师国内访问学者资金资助项目
关键词
车牌定位
HSV颜色特征
边缘检测
伴生与互补
目标真实性验证
license plate location
HSV color feature
edge detection
concomitant and complemence
object authenticity confirmation
