节点文献

基于深度图像处理技术的类圆形重叠颗粒计数

Counting of circular overlapping particles based on depth image processing technique

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 张健朱伟兴

【Author】 ZHANG Jian;ZHU Wei-xing;School of Electrical and Information Engineering,Jiangsu University;

【机构】 江苏大学电气信息工程学院

【摘要】 颗粒物计数的用途很广,但很费时且易出错,尤其是重叠时的颗粒物计数更加困难,而且由于技术和设备的限制,相关的研究也比较少。文中利用深度图像处理技术实现对重叠的类圆形颗粒物进行计数。首先采用Kinect相机对重叠目标采集图像,并且对采集的图像进行保存处理,将目标距离物体的实际距离与采集到的图片的灰度值进行映射,即目标与相机的距离越远,对应该点像素值越小。再对图像进行ROI提取和去噪,对图像进行预处理,求出分割阈值,将三维重叠目标计数问题转换为二维平面计数问题,简化研究问题的复杂性。文中采用高度大约为2cm、类圆形、大小均匀的砂糖橘作为研究目标。采用本文的研究思路得到目标二维平面区域后,采用Hough变换法进行圆形拟合,根据拟合结果得出重叠区域目标个数。实践表明,采用本文的方法能够满足重叠目标计数要求。

【Abstract】 Particle count is widely used,but it is time-consuming and error prone,especially in overlapping particles count,it is more difficult,and because of technical and equipment constraint,relatively few studies have been done. In this paper,the technique of depth image processing is used to count overlapped circular particles. Firstly,using Kinect camera captures images of overlapped objects.Then making a mapping between pixel value of object images and target space distance in real world,that is the farther between target and camera,the smaller of the gary. Then the depth image preprocessing is used to extract ROI and denoising,computing the segmentation thresholds. The 3 D overlap region is divided into two 2 D planar regions,the 3 D overlapping target counting is converted to a 2 D counting problem,simplifying the complexity of research questions. In this paper,cirtus,which is about uniformly2 cm high in size,is used as the research target. The Hough transform method is used for circle fitting,and the number of overlapping area targets is obtained according to the fitting result. The practice shows that this method can meet the requirement of overlapping target counting.

【关键词】 重叠深度图像计数Kinect相机拉普拉斯Hough变换
【Key words】 overlapdepth imagecountingKinect cameraLaplaceHough transform
【基金】 国家自然科学基金资助项目(31172243);江苏省高校优势学科建设项目(PAPD)
  • 【文献出处】 信息技术 ,Information Technology , 编辑部邮箱 ,2018年06期
  • 【分类号】TP391.41
  • 【被引频次】3
  • 【下载频次】251
节点文献中: 

本文链接的文献网络图示:

本文的引文网络