摘要
针对目前经编布花边切割传统手工加工方式的效率低下和产品质量不稳定的问题,提出了一种基于特征识别的经编布花边实时识别算法,此方法对图片进行自适应阈值处理,直线特征提取,图像分割,干扰轮廓去除,最终能够准确识别经编布的花边形状特征和精确位置,并且可以在复杂的工厂光照环境中保证识别的稳定性,并且通过对算法优化,大幅提高计算效率,可以满足实时性的要求,基于此算法开发的经编布花边视觉自动切割系统可以大幅的提高生产效率,提高产品质量。
Facing the problem of low efficiency and unstable quality in the traditional hand finishing tricot lace cutting field, a novel tricot lace real-time recognition method based on feature recognition is proposed. The method works by adaptive thresholding, line detection, image segmentation and reducing the fake contours, which can recognize accurately the profile features and locations of tricot laces. It has high stability even in complex factory lighting environment. It can satisfy the real-time request and promote computational efficiency by improving the computational efficiency of the method. The automatic vision cutting system based on the proposedmethod can highly improve production efficiency and quality.
出处
《激光与光电子学进展》
CSCD
北大核心
2015年第11期97-101,共5页
Laser & Optoelectronics Progress
基金
国家自然科学基金(51005090)
关键词
图像处理
模式识别
经编布花边
实时性
霍夫变换
image processing
pattern recognition
tricot lace
real-time
Hough transform
