基于改进GMM与帧差法的运动棉杂率分析算法研究  

Research on moving cotton impurity rate analysis algorithm based on improved GMM and frame difference method

作　　者：柴亚琴 刘秀平[1] 宋鑫 郭湛澎 胡道杰 刘高峰 CHAI Yaqin;LIU Xiuping;SONG Xin;GUO Zhanpeng;HU Daojie;LIU Gaofeng(School of Electronics and Information,Xi′an Polytechnic University,Xi'an,Shaanxi 710048,China)

机构地区：[1]西安工程大学电子信息学院,陕西西安710048

出　　处：《光电子．激光》2024年第2期171-179,共9页Journal of Optoelectronics·Laser

基　　金：陕西省科技厅项目(2018GY-173);西安市科技局项目(GXYD7.5)资助项目。

摘　　要：针对清梳棉流程中产出棉含杂高、质量差的问题,结合改进高斯混合模型(Gaussian mixed model, GMM)与帧差法,提出一种局部运动棉杂率控制优化方法。首先针对清棉机除杂原理及棉杂特性进行分析;其次通过提取视频关键帧并改进GMM与帧差法对图像序列“与”运算实现目标的精确提取,进而通过设计GMM分类器获得棉杂率并进行分析;最后与传统的检测算法作对比验证。实验表明,改进后的算法在有效性以及实用性方面优于传统算法。同时,通过引入闭环控制能满足工业高精度、实时性的需求。To solve the problem of high trash content and poor quality of the output cotton in the cleaning and combing process,a local motion impurity ratio control optimization method is proposed by combining the improved Gaussian mixed model(GMM)and frame difference method.Firstly,the principle of the cleaning machines and the characteristics of the trash is analyzed cotton.Secondly,by extracting the key frames of the video,and combining the improved GMM and the frame difference method,the target is accurately extracted by the"with"operation of the image sequence,and then by designing the GMM classifier to obtain the cotton impurity rate for analysis.Finally,it is compared with the traditional detection algorithm for validation.Experiments show that the improved algorithm is better than the traditional algorithm in terms of effectiveness as well as practicality.At the same time,it can meet industrial high precision and real-time requirements by introducing closed-loop control.

关 键 词：运动目标检测 棉杂率分析 关键帧提取 高斯混合模型 帧差法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]