摘要
针对纱线高速运动时无法实时准确检测疵点的问题,提出了一种高速纱线的实时疵点检测算法,该算法适用于实时处理大容量图像和高速移动纱线疵点检测。该算法通过将对称差分算法和连通域特征匹配方法相结合,提高了纱线疵点检测准确性,同时缩短了处理时间。首先对图像进行了预处理,再使用对称差算法分解疵点图像并提取了图像疵点特征,然后使用连通域特征匹配方法识别了疵点。改进了传统差分算法无法抗抖动缺点,比较完整地保留了疵点信息,构造了识别能力特别强的特征匹配方法。最后,将该算法疵点检测的准确性和检测速度与现有检测方法进行了对比分析。研究结果表明,该算法在准确性方面优于人工检测及传统差分算法,检测速度相对神经网络和传统差分算法有所提高,该算法能够在实现实时、快速检测疵点的同时保证检测疵点检测的准确性。
Aiming at the problems of a real-time defect detection algorithm for high-speed yarn, this algorithm was used to solve the defect problem of real-time to accurately detecting. The algorithm was suitable for real-time processing of large-volume image and high-speed moving yarn defect detection. By the symmetrical differencing algorithm and connected component matching, the algorithm was combined to improve the yarn defect detection accuracy while reducing processing time. Firstly, image needed preprocessing, then images were decomposed and extracted by using symmetrical differencing algorithm, and then, defects were recognized by using the connected component. The shortcoming of anti-tremble of the traditional differential algorithm was improved. Component matching method with particularly strong ability of identifying was constructed. Finally, the algorithm＇s defect detection accuracy and detection speed were compared with existing detection methods analysis. The results indicate that this algorithm is better than manual detection and traditional algorithms, detection speed relative to the neural network and the traditional algorithms has been improved. It is considered that the algorithm is able to achieve real-time rapid detection of defects at the same time ensure the detection accuracy of defect detection.
出处
《机电工程》
CAS
2013年第8期1010-1014,1019,共6页
Journal of Mechanical & Electrical Engineering
基金
浙江省重点科技创新团队资助项目(2010R50008)
关键词
疵点检测
实时处理
高速移动纱线
对称差分算法
连通域特征
defect detection
real-time processing
high-speed moving yarn
symmetrical differencing algorithm
connected component
