昆明理工大学
TP391.4???
国家自然科学基金项目（面上项目，重点项目，重大项目）
College of Mechanical and Electrical Engineering,Kunming University of Science and Technology
针对品检机上的小盒烟标的色差在线检测存在速度慢的问题，提出了一种基于k-means聚类的烟标色差在线检测方法。该方法基于图像处理和机器视觉，通过对CCD相机采集到的标准样张和待检测烟标的主背景色进行识别，然后通过颜色空间转换，最后进行色差的检测，色差小于4.0的为合格烟标。实验结果表明，由于不需要背景去除和图像配准，该方法检测速度优于其他算法，且准确率能够满足实际生产需要。
Aiming at the problem that the online detection of chromatic aberration of small box cigarette case on the quality inspection machine is slow, an online detection method of cigarette label chromatic aberration based on k-means clustering is proposed. Based on image processing and machine vision, this method identifies the standard sample collected by the CCD camera and the main background color of the cigarette scale to be detected, and then converts through the color space, and finally performs the detection of chromatic aberration, and the chromatic aberration is less than 4.0 for the qualified cigarette case. Experimental results show that because there is no need for background removal and image registration, the detection speed of this method is better than that of other algorithms, and the accuracy can meet the actual production needs.
