改进二维OTSU和自适应遗传算法的红外图像分割
发布时间：2019-05-17 17:54
【摘要】：为提高电路板热红外图像分割效果,解决电路板故障诊断的问题,提出了一种将自适应遗传算法和改进二维OTSU算法相结合的新算法。自适应遗传算法采取快速排序法,利用遗传代数的变化改进交叉、变异概率;根据邻域像素点与中心像素点之间的距离对二维OTSU邻域均值算法的比例系数进行加权,判断噪声点并对热红外图像进行降噪处理;引入类内方差法,对阈值进行优化。利用了遗传算法的并行性和强大的空间搜索能力,提高了二维OTSU的阈值查找速度,提高了热红外图像的分割效率。实验结果表明,该算法提高了热红外图像的分割准确度,有一定的应用前景。
[Abstract]:In order to improve the thermal infrared image segmentation effect of circuit board and solve the problem of circuit board fault diagnosis, a new algorithm combining adaptive genetic algorithm with improved two-dimensional Otsu algorithm is proposed. The adaptive genetic algorithm adopts the fast sorting method to improve the cross and mutation probability by using the change of genetic algebra. According to the distance between neighborhood pixel and central pixel, the proportional coefficient of two-dimensional OTSU neighborhood mean algorithm is weighted, the noise point is judged and the thermal infrared image is de-noised, and the intra-class variance method is introduced to optimize the threshold. By using the parallelism of genetic algorithm and strong spatial search ability, the threshold search speed of two-dimensional Otsu is improved, and the segmentation efficiency of thermal infrared image is improved. The experimental results show that the algorithm improves the segmentation accuracy of thermal infrared image and has a certain application prospect.
【作者单位】： 中国民航大学;
【基金】：国家自然科学基金(U1333111,61405246) 中国民航大学中央高校项目(3122016D018)
【分类号】：TN21;TP391.41
本文编号：2479296
[Abstract]:In order to improve the thermal infrared image segmentation effect of circuit board and solve the problem of circuit board fault diagnosis, a new algorithm combining adaptive genetic algorithm with improved two-dimensional Otsu algorithm is proposed. The adaptive genetic algorithm adopts the fast sorting method to improve the cross and mutation probability by using the change of genetic algebra. According to the distance between neighborhood pixel and central pixel, the proportional coefficient of two-dimensional OTSU neighborhood mean algorithm is weighted, the noise point is judged and the thermal infrared image is de-noised, and the intra-class variance method is introduced to optimize the threshold. By using the parallelism of genetic algorithm and strong spatial search ability, the threshold search speed of two-dimensional Otsu is improved, and the segmentation efficiency of thermal infrared image is improved. The experimental results show that the algorithm improves the segmentation accuracy of thermal infrared image and has a certain application prospect.
【作者单位】： 中国民航大学;
【基金】：国家自然科学基金(U1333111,61405246) 中国民航大学中央高校项目(3122016D018)
【分类号】：TN21;TP391.41
【相似文献】
相关期刊论文 前8条
1 官伯林;贾建援;朱应敏;;基于自适应遗传算法的三轴光电跟踪策略[J];仪器仪表学报;2012年08期
2 苏琳琳;张晓林;;利用自适应遗传算法的芯片功能验证自动测试[J];应用科学学报;2011年06期
3 金力;刘桥;;基于自适应遗传算法的运放的电路级综合[J];西华大学学报(自然科学版);2006年02期
4 兰海;汪宇涵;张利军;;基于改进自适应遗传算法的船舶电力系统滤波装置优化配置[J];船电技术;2009年06期
5 许川佩;陈征南;任智新;胡聪;;基于云自适应遗传算法的NoC路径分配研究[J];计算机测量与控制;2012年09期
6 许川佩;陈征南;任智新;;基于云自适应遗传算法的NoC映射研究[J];计算机工程与应用;2012年36期
7 赵曙光,刘贵喜,杨万海;利用自适应遗传算法实现模拟电路自动设计[J];西安电子科技大学学报;2003年03期
8 ;[J];;年期
相关硕士学位论文 前3条
1 柯家伟;面向订单快速交付的生产过程管控技术研究与系统实现[D];北京理工大学;2016年
2 陈殿夏;桥式网络系统可靠性分析和优化[D];沈阳工业大学;2005年
3 金力;基于改进自适应遗传算法的CMOS运放的电路级综合方法的研究[D];贵州大学;2006年
，本文编号：2479296
本文链接：https://www.wllwen.com/kejilunwen/dianzigongchenglunwen/2479296.html
