摘要
在基于机器视觉的炮膛疵病检测中,针对计算机不能以"目标分割-特征提取-特征分析-判定"的经典思路实现疵病图像识别的难题,采用二次谱分析方法从图像全局性特点中挖掘疵病的信息。定义图像二次谱为"图像功率谱的对数幅值谱",提取其亮线长宽比以及谱图能量均值、能量方差和能量矩4个参量来分析炮膛图像中是否存在疵病。通过实验验证了参量的有效性。
In gun bore flaw detection based on machine vision, computer can not recognize flaw image with typical idea, such as target segmentation, feature extraction, feature analysis and judgment. Aiming at this problem, twice-spectrum analysis method was adopted to extract flaw information from overall features of image. Image twice-spectrum was defined as logarithmic amplitude spectrum of power spectrum. And four parameters, which were Length-to-Width Ratio of Bright Straight Line, Energy Mean, Energy Variance and Energy Moment, were extracted to analyze gun bore images. The experimental results testify rationality of the parameters.
出处
《光电工程》
CAS
CSCD
北大核心
2010年第5期37-40,79,共5页
Opto-Electronic Engineering
基金
军队科研计划资助项目
关键词
机器视觉
疵病图像识别
炮膛
功率-幅值谱
machine vision
flaw image recognition
gun bore
power-amplitude spectrum
