Computer Science ›› 2018, Vol. 45 ›› Issue (8): 218-222.doi: 10.11896/j.issn.1002-137X.2018.08.039

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Intelligent Geometry Size Measurement System for Logistics Industry

LI Juan, ZHOU Fu-qiang, LI Zuo-xin, LI Xiao-jie   

  1. School of Instrumentation Science and Opto-electronics Engineering,Beihang University,Beijing 100191,China
  • Received:2017-05-01 Online:2018-08-29 Published:2018-08-29

Abstract: The rapid development of Internet and e-commerce has brought disruptive change of logistics industry.However,there are still some problems for logistics industry,such as high cost,low technical equipment and low efficiency in the distribution system.For a long time,the use of goods’ geometry information,which can be very helpful in improving packing,classification and transport,is a weak process in logistics industry.Focusing on the above problems,this paper built an intelligent system to measure geometry size of logistic goods.Based on stereo vision system and by the combination of disparity algorithm for 3D reconstruction and feature extraction algorithm, the system computes the geometry size for general logistics in complex background and is less affected by light.The experimental results show that this system can be implemented to compute the geometry size quickly for the logistics industry,and its mean measurement error is less than 2% and maximum error is less than 3%,which can meet the basic requirement of logistics.

Key words: Logistics industry, Geometry size, Stereo vision, Feature extraction

CLC Number: 

  • TP391
[1]SUN D F.Discussion on Reducing the Cost of Logistic Enterprises .China Economist,2011(4):185-186.(in Chinese)孙德凤.关于降低物流企业成本的探讨[J].经济师,2011(4):185-186.
[2]ZHOU J.Research on Optimization of the Key-Link in Self-support Logistics Distribution.Beijing:North China Electric Power University,2016.(in Chinese)周洁.自营物流配送系统关键环节优化研究[D].北京:华北电力大学,2016.
[3]LU F.Design and Implementation of Amazon Logistics LineHaul Settlement System.Beijing:Beijing Jiaotong University,2015.(in Chinese)卢飞.亚马逊物流干线运输结算系统的设计与实现[D].北京:北京交通大学,2015.
[4]YUAN Z Y.Automatic Size Measurement Device of DeliverSupplies.Industrial Instrumentation & Automation,1995(3):56.(in Chinese)袁志毅.测量运送物尺寸重量的自动计量装置──“测量架”[J].工业仪表与自动化装置,1995(3):56.
[5]Sensor Intelligence.Volume-weight Measurement and Bar Code Scanning System.Maschinen Markt,2016(38):63.(in Chinese)广州市西克传感器有限公司.体积重量测量及条码扫描系统[J].现代制造,2016(38):63.
[6]张广军.视觉测量.北京:科学出版社,2008:33-36.
[7]WENG J,COHEN P,HERNIOU M.Camera calibration withdistortion models and accuracy evaluation.IEEE Transactions on Pattern Analysis & Machine Intelligence,1992,14(10):965-980.
[8]张广军.视觉测量.北京:科学出版社,2008,134-135.
[9]YANG J.Research on Binocular Stereo Vision MeasurementTechnology.Xi’an:Xi’an University of Technology,2017. (in Chinese)杨洁. 双目立体视觉测距技术研究.西安:西安理工大学,2017.
[10]LIU Q H.Theoretical and Experimental Research on 3D SizeMeasurement of High-temperature Components Based on Infrared Vision.Tianjin:Tianjin University,2011. (in Chinese)刘启海. 高温构件三维尺寸红外视觉测量的理论和实验研究.天津:天津大学,2011.
[11]WEN Z,ZHANG X,ZHOU C S,et al.Modified Edge Detection Algorithm based on Canny.Communications Technology,2017,50(10):2236-2240.(in Chinese)文章,张欣,周昌顺,等.一种基于Canny的边缘检测改进算法.通信技术,2017,50(10):2236-2240.
[12]HUANG S H,BI Y W,LIU D T,et al.Research on Noncontact Measurement Based on Binocular Stereo Vision.Journal of Yantai University(Natural Science and Engineering Edition),2017,30(4):323-327. (in Chinese)黄松梅,毕远伟,刘殿通,等.双目立体视觉非接触式测量研究.烟台大学学报(自然科学与工程版),2017,30(4):323-327.
[13]FUSIELLO A,TRUCCO E,VERRI A.A compact algorithm for rectification of stereo pairs.Machine Vision & Applications,2000,12(1):16-22. ZHANG Z Y.A Flexible New Technique for Camera Calibration.IEEE Transactions on Pattern Analysis & Machine Intelligence,2000,22(11):1330-1334. GUNEY F,GEIGER A.Displets:Resolving stereo ambiguities using object knowledge∥Computer Vision and Pattern Re-cognition.IEEE,2015:4165-4175.KANADE T,OKUTOMI M.A Stereo Matching Algorithmwith an Adaptive Window:Theory and Experiment.IEEE Computer Society,1994,16(9):920-932. HIRSCHMULLER H.Stereo Processing by Semiglobal Matching and Mutual Information.IEEE Transactions on Pattern Analysis & Machine Intelligence,2007,30(2):328-341.
[18]WANG C Y.Research on Point Cloud Mosaic Algorithm in 3D Reconstruction.Taiyuan:North University of China,2017.(in Chinese)王程远.三维重建中的点云拼接算法研究.太原:中北大学,2017.
[19]LIANG Q X.A Research Based on 3D Point Cloud Data Surface Reconstruction of Laser Radar.Beijing:Beijing Jiaotong University,2012. (in Chinese)梁群仙. 基于激光雷达三维点云数据曲面重构技术的研究.北京:北京交通大学,2012.
[20]YANG Z R.Research on Stereo Matching Approaches and Occlusion in Binocular Vision.Qihuangdao:Yanshan University,2010.(in Chinese)杨志荣.双目视觉立体匹配方法和遮挡问题研究. 秦皇岛:燕山大学,2010.
[1] ZHOU Yan, ZENG Fan-zhi, WU Chen, LUO Yue, LIU Zi-qin. 3D Shape Feature Extraction Method Based on Deep Learning [J]. Computer Science, 2019, 46(9): 47-58.
[2] DU Zhen, MA Li-peng, SUN Guo-zi. Network Traffic Anomaly Detection Based on Wavelet Analysis [J]. Computer Science, 2019, 46(8): 178-182.
[3] SHE Rong-rong, ZHANG Li-ping. Method for Identifying and Recommending Reconstructed Clones Based on Software Evolution History [J]. Computer Science, 2019, 46(8): 224-232.
[4] HAN Hui,WANG Li-ming,CHAI Yu-mei,LIU Zhen. Text Sentiment Classification Based on Deep Forests with Enhanced Features [J]. Computer Science, 2019, 46(7): 172-179.
[5] LI Yue-feng. 3D Retrieval Algorithm Based on Multi-feature [J]. Computer Science, 2019, 46(6A): 266-269.
[6] HAN Xiao, ZHANG Jing, LI Yue-long. Gesture Recognition Based on Hand Geometric Distribution Feature [J]. Computer Science, 2019, 46(6A): 246-249.
[7] HE Xiao-wen, HU Yi-fei, WANG Hai-ping, CHEN Mo. Online Learning Nonnegative Matrix Factorization [J]. Computer Science, 2019, 46(6A): 473-477.
[8] ZHOU Bin-bin, ZHANG Hong-jun, ZHANG Rui, FENG Yun-tian, XU You-wei. Construction of Military Corpus for Entity Annotation [J]. Computer Science, 2019, 46(6A): 540-546.
[9] MENG Zhi-qing, XU Wei-wei. Temporal Text Data Stream Feature Trend Model and Algorithm [J]. Computer Science, 2019, 46(6A): 417-422.
[10] XU Lei, WANG Jian-xin. Data Mining Algorithm of Abnormal Network Based on Fuzzy Neural Network [J]. Computer Science, 2019, 46(4): 73-76.
[11] LIU Xiao-hong, ZHU Yu-quan, LIU Zhe, SONG Yu-qing, ZHU Yan, YUAN De-qi. Liver CT Image Feature Extraction Method Based on Improved Multi-scale LBP Algorithm [J]. Computer Science, 2019, 46(3): 125-130.
[12] LI Yin-min, XUE Kai-xin, GAO Zan, XUE Yan-bin, XU Guang-ping, ZHANG Hua. 3-D Model Retrieval Algorithm Based on Residual Network [J]. Computer Science, 2019, 46(3): 148-153.
[13] CHEN Wei, LIU Yan, LEI Qing. Classification of Small Difference Behavior Characteristics Based on Intelligent Vision [J]. Computer Science, 2019, 46(3): 298-302.
[14] SHENG Lei, WEI Zhi-hua, ZHANG Peng-yu. Multi-layer Object Detection Algorithm Based on Multi-source Feature Late Fusion [J]. Computer Science, 2019, 46(2): 249-254.
[15] DING Hong-wei, WAN Liang, ZHOU Kang, LONG Ting-yan, XIN Zhuang. Study on Intrusion Detection Based on Deep Convolution Neural Network [J]. Computer Science, 2019, 46(10): 173-179.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] . [J]. Computer Science, 2018, 1(1): 1 .
[2] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[3] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[4] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[5] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[6] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[7] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[8] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[9] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[10] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .