摘要
针对类圆形目标图像识别方法的不足,以轧钢厂成捆棒材图像为实例,提出了不规则类圆形团块目标模式识别新方法,设计了边缘检测、中心增强和重心聚合等一系列算法,以实现计算机对类圆形目标图像的自动识别与检测。研究结果表明:以新算法为核心技术的软件能够对直径为12～40cm的棒材进行计数,点支准确的捆精度达到99%,且每捆计数时间少于3s。
Aimed at the disadvantages of the existing methods of identifying the round type images, a new method of identifying the round type particle target was put forward by an example of stick bundle images in factory. A series of algorithms,such as the border detection, the center enhancement and the convergence of center of gravity were designed to realize the automatic identification and detection of the images by computer. The software designed based on the above alorithms can count the sticks whose diameter is from 12 cm to 40 cm. The precision is 99% and the counting time for each bundle is less than 3 s.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2004年第4期632-637,共6页
Journal of Central South University:Science and Technology
基金
国家高技术"863"项目(863 511 9702 412)
关键词
图像处理
边缘检测
聚类
类圆形
模式识别
image process
edge detection
clustering
quasi-circular object
pattern recognition
