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。
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.
出处
《电脑开发与应用》
2015年第3期48-50,共3页
Computer Development & Applications
关键词
钢筋端面图像
图像增强
自适应阈值
end image of steel bar
image enhancement
adaptive threshold
