改进的自适应分割算法在钢筋图像中的应用
Improved Adaptive Segmenting Algorithm for Steel Bar Image
臧晶 1郭倩倩 1李武举1
作者信息
- 1. 沈阳理工大学信息科学与工程学院，沈阳 110159
- 折叠
摘要
为提高复杂条件下成捆钢筋端面图像的分割效果，先进行非均匀光照校正和噪声滤除，提出了新的阈值搜索范围和新的阈值计算准则寻找最佳阈值，改进了自适应阈值算法，并对端面图像进行分割，最后借助Matlab对该算法进行了仿真。实验结果表明，新算法不仅缩短了运算时间，而且有效去除非均匀光照、噪声等因素的干扰，突出了图像内部的细节，有利于后续的钢筋识别和计数。
Abstract
In order to enhance segmentation result,the end image of bundled steel bar under complicated condition is corrected non-uniform illumination and filtered noise firstly,and a new threshold searching scope and a new threshold criterion for finding the best threshold are put forward to improve maximum between-cluster variance algorithm.Then the end image is segmented through the new method. Finally,it is simulated by Matlab.The experiment results show that the new algorithm not only shortens operation time,but also effectively reduces the interference of uniform illumination and noise. It highlights the details inside the image and contributes to subsequently steel bar identification and counting.
关键词
钢筋端面图像/图像增强/自适应阈值Key words
end image of steel bar/image enhancement/adaptive threshold引用本文复制引用
出版年
2015
NETL
NSTL
维普
万方数据