基于特征块匹配的医用注射液图像位移补偿应用

doi:10.7517/j.issn.1674-0475.2016.06.541

影像科学与光化学 ›› 2016, Vol. 34 ›› Issue (6): 541-551.DOI: 10.7517/j.issn.1674-0475.2016.06.541

基于特征块匹配的医用注射液图像位移补偿应用

阮峰, 张辉, 李宣伦, 李若云

长沙理工大学电气与信息工程学院, 湖南长沙 410004

收稿日期:2016-06-12 出版日期:2016-11-15 发布日期:2016-11-15
通讯作者: 张辉
基金资助:
国家科技支撑计划项目（2015BAF11B01）、国家自然科学基金项目（61401046）、湖南省自然科学基金项目（13JJ4058）、湖南省教育厅资助科研项目（13B135）和长沙市科技计划项目（K1404019-11）资助

Application of Image Displacement Compensation Based on Feature Block Matching for Medical Injection

RUAN Feng, ZHANG Hui, LI Xuanlun, LI Ruoyun

College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410004, Hunan, P. R. China

Received:2016-06-12 Online:2016-11-15 Published:2016-11-15

摘要/Abstract

摘要：

针对机器视觉药液异物检测机器人由于机械振动或跟踪不同步，导致所拍摄的序列图像产生位移偏差、影响后续异物分割与提取的问题，本工作采取特征点匹配与块匹配相结合的方法，对序列图像进行配准，求出运动矢量进行图像位移补偿，克服了传统特征点匹配产生空间位置偏差较大误匹配、传统块匹配需对背景静止块进行预处理以及单独使用特征点对匹配或块匹配均难以满足实时需要的问题。首先，对参考帧进行FAST特征点检测，再利用Hessian矩阵、非极大值抑制、熵值差法和特征点距离约束选取稳定的特征点；然后，根据特征点位置信息，选取以特征点为中心的待匹配宏块，再采用一种改进的偏水平方向的六边形搜索策略（HHS）与当前帧进行块与块的匹配，找到最佳匹配块；最后，利用匹配块之间的坐标参数求出运动参数，再利用求出的运动矢量进行帧间补偿。实验结果表明，该算法实时性能能达到72 ms，远快于点对匹配中ORB算法的140 ms，比直接用原有的六边形搜索算法（HS）进行块匹配快了近20%，兼顾了速度与精度，能快速补偿药瓶在图像中的位移偏差，抑制图像位移偏差所引起的各种干扰。

关键词: 机器视觉, 异物检测机器人, 特征点检测, 块匹配, 搜索策略, 运动补偿

Abstract:

The sequence images captured by the intelligent light inspection machine had the displacement deviation caused by mechanical vibration or tracking asynchronization, which affected the subsequent foreign body segmentation and extraction. To obtain the motion vectors to compensate for the image displacement, the method of feature point detection and block matching is adopted. Firstly, the reference frame was detected by FAST feature points, and used the non-maximal suppression,Hessian matrix,the entropy difference and distance constraint to select stable feature points. According to the location information of the feature points, the matching block were selected, of which the center was located by the feature points. Then, an improved horizontal direction search strategy(HHS) was used to match the current frame to find the best matching block. Finally, the motion parameters were obtained, and the motion vectors were obtained. Experimental results show that the real-time performance of this algorithm is 72 ms, much more faster than the 140 ms algorithm of ORB, and faster than the direct use of the original Hexagonal Search(HS) algorithm for block matching nearly 20%. The accuracy is higher than the feature point matching algorithms. Our algorithm overcomed these problems: 1. the traditional feature point matching could produce a large spatial deviation error matching; 2. the traditional block matching need to preprocess the static background blocks; 3. it is difficult to meet the needs of real time for single feature point matching or block matching. Considering the speed and precision, this algorithm can rapidly compensate the displacement deviation in the image of the bottle, and suppress the interference caused by the deviation of the image displacement.

Key words: machine vision, foreign body detection robot, feature point detection, block matching, search strategy, motion compensation

阮峰, 张辉, 李宣伦, 李若云. 基于特征块匹配的医用注射液图像位移补偿应用[J]. 影像科学与光化学, 2016, 34(6): 541-551.

RUAN Feng, ZHANG Hui, LI Xuanlun, LI Ruoyun. Application of Image Displacement Compensation Based on Feature Block Matching for Medical Injection[J]. Imaging Science and Photochemistry, 2016, 34(6): 541-551.

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基于特征块匹配的医用注射液图像位移补偿应用

Application of Image Displacement Compensation Based on Feature Block Matching for Medical Injection

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