A computer vision-based shape-classification system using image projection and a neural network

被引：13
|
作者：
Hou, TH [1 ]
Pern, MD [1 ]
机构：
[1] Natl Yunlin Univ Sci & Technol, Inst Ind Engn & Management, Yunlin, Taiwan
来源：
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 1999年 / 15卷 / 11期
关键词：
image projection; neural networks; shape classification;
D O I：
10.1007/s001700050141
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this research, a computer vision-based shape-recognition system which combines an image projection and the back propagation neural network is proposed. The system uses the image projection and features of the projection histogram to represent the shape, and uses the back propagation neural network to classify the shape. In this research, a fast normalisation scheme is developed which is especially designed for the image projection. II can find the same projection axis no matter how the object is oriented. Therefore, the proposed system can be invariant to scale, translation, and orientation variations. This research finds that the direct representation scheme of the back propagation neural net has better accuracy that? the binary coding representation scheme. This research also finds that classification accuracy of the proposed system is greater than 98.8% and its processing speed is also very fast. Therefore, the proposed system is feasible for use in shape classification.
引用
收藏
页码：843 / 850
页数：8
相关论文
共 50 条
  • [41] Classification of Rock Joint Profiles Using an Artificial Neural Network-Based Computer Vision Technique
    Xu Zhu
    Jiaxuan Zhang
    Joung Oh
    Guangyao Si
    Hamid Roshan
    Rock Mechanics and Rock Engineering, 2024, 57 : 3083 - 3090
  • [42] Vision-based Network System for Industrial Applications
    Suesut, Taweepol
    Numsomran, Arjin
    Tipsuwanporn, Vittaya
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 12, 2006, 12 : 98 - 102
  • [43] Classification of Rock Joint Profiles Using an Artificial Neural Network-Based Computer Vision Technique
    Zhu, Xu
    Zhang, Jiaxuan
    Oh, Joung
    Si, Guangyao
    Roshan, Hamid
    ROCK MECHANICS AND ROCK ENGINEERING, 2024, 57 (04) : 3083 - 3090
  • [44] Vision-based Traffic Sign Compliance Evaluation using Convolutional Neural Network
    Roxas, Edison A.
    Acilo, Joshua N.
    Vicerra, Ryan Rhay P.
    Dadios, Elmer P.
    Bandala, Argel A.
    PROCEEDINGS OF 4TH IEEE INTERNATIONAL CONFERENCE ON APPLIED SYSTEM INNOVATION 2018 ( IEEE ICASI 2018 ), 2018, : 120 - 123
  • [45] Vision-based MAV Navigation in Underground Mine Using Convolutional Neural Network
    Mansouri, Sina Sharif
    Karvelis, Petros
    Kanellakis, Christoforos
    Kominiak, Dariusz
    Nikolakopoulos, George
    45TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2019), 2019, : 750 - 755
  • [46] Improved Vision-Based Detection of Strawberry Diseases Using a Deep Neural Network
    Kim, Byoungjun
    Han, You-Kyoung
    Park, Jong-Han
    Lee, Joonwhoan
    FRONTIERS IN PLANT SCIENCE, 2021, 11
  • [47] Mango Fruit Sortation System using Neural Network and Computer Vision
    Yossy, Emny Harna
    Pranata, Jhonny
    Wijaya, Tommy
    Hermawan, Heri
    Budiharto, Widodo
    DISCOVERY AND INNOVATION OF COMPUTER SCIENCE TECHNOLOGY IN ARTIFICIAL INTELLIGENCE ERA, 2017, 116 : 596 - 603
  • [48] Home Surveillance System using Computer Vision and Convolutional Neural Network
    Zhang, Xin
    Yi, Won-Jae
    Saniie, Jafar
    2019 IEEE INTERNATIONAL CONFERENCE ON ELECTRO INFORMATION TECHNOLOGY (EIT), 2019, : 266 - 270
  • [49] Shape extraction and classification of plankton using computer vision
    Wang, N
    Yu, XS
    Tang, Y
    2005 Beijing International Conference on Imaging: Technology and Applications for the 21st Century, 2005, : 186 - 187
  • [50] Computer vision-based orthorectification and georeferencing of aerial image sets
    Faraji, Mohammad Reza
    Qi, Xiaojun
    Jensen, Austin
    JOURNAL OF APPLIED REMOTE SENSING, 2016, 10
12345