摘要
枪弹弹底底火检测是枪弹质量控制的核心,为了有效分割弹底底火表面缺陷图像,提出一种新的分割方法。该方法针对弹底检测要求及弹底图像基本特征,首先大致确定待检测的底火部分图像,对其运用Log算子进行边缘检测确定底火圆边缘;然后分析了Hough变换和最小二乘法圆拟合的圆检测算法的各自优缺点,提出了改进Hough变换和最小二乘法圆拟合相结合的圆检测算法,以获得较精确的底火圆圆心和半径;最后利用底火圆圆心和半径提取底火圆图像,利用统计阈值分割底火表面缺陷,利用数学形态学优化分割结果。通过实验表明,运用此方法分割弹底底火表面缺陷,平均误分割率低于10%,平均偏差小于17个像素,表现出较好的准确性和鲁棒性。
The checking of bullet＇s primer is the most important step in controlling the quality of bullet products. In order to segment the image of bullet＇s primer surface defect accurately, a new method of image segmentation was proposed. According to the checking requirement and the properties of cartridge＇s bottom, firstly, the image of bullet＇s primer was ascertained approximately to be detected, and Log operator was applied to extract the circle edge of primer. After analyzing both advantages and disadvantages of the Hough transform and the least square method, a new algorithm of circle detection combined improved Hough transform and the least square method was proposed, by which the center of circle and radius were acquired accurately. Finally, the image of primer circle was extracted by the parameters of circle, the primer surface defect was segmented by threshold, and the results of segmentation were optimized by mathematical morphology. The experimental results show that the proposed method is of accuracy and robustness in the application of bullet＇s primer surface defect segmentation. The average wrong segmentation rate is below 10%, and the average deviation is less than 17 oixels.
出处
《计算机应用》
CSCD
北大核心
2012年第8期2320-2323,共4页
journal of Computer Applications
关键词
弹底底火
边缘检测
圆检测
图像分割
数学形态学
bullet＇s primer
edge detection
circle detection
image segmentation
mathematical morphology
