摘要
针对遥控器缺陷检测中待测样品图像可能出现的平移、旋转变化造成误检率过高的问题,提出了一种基于SURF(Speeded Up Robust Feature)算法的遥控器缺陷自动检测方法。上述方法首先利用SURF提取特征点,其次采用分块匹配对原匹配算法进行改进,实现特征点的加速匹配并消除误匹配点,根据匹配得到的单应性矩阵求得校正后的图像,得到校正图与模板图的差分图。对差分图进行二值化和形态学处理,标注缺陷位置。实验结果表明,所提出的算法能有效检测出遥控器中的缺陷,并对旋转、平移等具有较好的鲁棒性。实验平均检测时间为0.82s,达到了实时性的要求,具有一定的应用价值。
To deal with the problem of high false detection rate due to the changes of translation and rotation, a method for automatic defect detection based on SURF for remote control was proposed. Firstly, the SURF feature detector was used to gain the interest points, then a method of matching based on blocking was improved to accelerate the match and eliminate the mismatching points. According to the homographic matrix, the detection image can be corrected. Then, difference image by subtracting standard image to the corrected image was processed by binarization and morphological opening operation, which finally results in the defect location marking. The experimental results show that the proposed algorithm can effectively detect the defects of remote control and is robust to the changes of translation and rotation. The average detection time is 0.8s, which can meet the requirement of real-time system and is of some application value.
出处
《计算机仿真》
CSCD
北大核心
2015年第11期420-424,共5页
Computer Simulation
基金
中国科学院战略性先导专项基金项目(XDA06020700)
关键词
缺陷检测
图像处理
分块
差影法
Defect detection
Image process
Blocking
Subtraction method