Real time fabric defect detection system on an embedded DSP platform

被引:35
|
作者
Raheja, Jagdish Lal [1 ]
Ajay, Bandla [2 ]
Chaudhary, Ankit [3 ]
机构
[1] CEERI CSIR, Machine Vis Lab, Pilani, Rajasthan, India
[2] BITS, Dept Elect & Elect Engn, Pilani, Rajasthan, India
[3] Univ Iowa, Dept Elect & Comp Engn, Iowa City, IA 52242 USA
来源
OPTIK | 2013年 / 124卷 / 21期
关键词
Fabric defects; Texture; Gray level co-occurrence matrix; DSP kit; Energy computation; Sliding window; FDDS;
D O I
10.1016/j.ijleo.2013.03.038
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In industrial fabric productions, automated real time systems are needed to find out the minor defects. It will save the cost by not transporting defected products and also would help in making company image of quality fabrics by sending out only undefected products. A real time fabric defect detection system (FDDS), implemented on an embedded DSP platform is presented here. Textural features of fabric image are extracted based on gray level co-occurrence matrix (GLCM). A sliding window technique is used for defect detection where window moves over the whole image computing a textural energy from the GLCM of the fabric image. The energy values are compared to a reference and the deviations beyond a threshold are reported as defects and also visually represented by a window. The implementation is carried out on a TI TMS320DM642 platform and programmed using code composer studio software. The real time output of this implementation was shown on a monitor. (C) 2013 Elsevier GmbH. All rights reserved.
引用
收藏
页码:5280 / 5284
页数:5
相关论文
共 50 条
  • [1] Intelligent real-time fabric defect detection
    Castilho, Hugo Peres
    Sequeira Goncalves, Paulo Jorge
    Caldas Pinto, Joao Rogerio
    Serafim, Antonio Limas
    [J]. IMAGE ANALYSIS AND RECOGNITION, PROCEEDINGS, 2007, 4633 : 1297 - +
  • [2] Real-time portable system for fabric defect detection using an ARM processor
    Fernandez-Gallego, J. A.
    Yanez-Puentes, J. P.
    Ortiz-Jaramillo, B.
    Alvarez, J.
    Orjuela-Vargas, S. A.
    Philips, W.
    [J]. OPTICS, PHOTONICS, AND DIGITAL TECHNOLOGIES FOR MULTIMEDIA APPLICATIONS II, 2012, 8436
  • [3] Real-time lane detection and departure warning system on embedded platform
    Lee, Youngwan
    Kim, Hakil
    [J]. 2016 IEEE 6TH INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - BERLIN (ICCE-BERLIN), 2016,
  • [4] Real time fabric defect detection by using fourier transform
    Hanbay, Kazim
    Talu, Muhammed Fatih
    Ozguven, Omer Faruk
    [J]. JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, 2017, 32 (01): : 151 - 158
  • [5] Real-time license plate recognition on an embedded DSP-Platform
    Arth, Clemens
    Limberger, Florian
    Bischof, Horst
    [J]. 2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8, 2007, : 3153 - +
  • [6] Real time fabric defect detection system on Matlab and C plus plus /Opencv platforms
    Hanbay, Kazim
    Golgiyaz, Sedat
    Talu, Muhammed Fatih
    [J]. 2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP), 2017,
  • [7] Real-time vision system for defect detection and neural classification of web textile fabric
    Mitropulos, P
    Koulamas, C
    Stojanovic, R
    Koubias, S
    Papadopoulos, G
    Karayanis, G
    [J]. MACHINE VISION APPLICATIONS IN INDUSTRIAL INSPECTION VII, 1999, 3652 : 59 - 69
  • [8] Fabric4show: real-time vision system for fabric defect detection and post-processing
    Huaizhou Lin
    Dan Cai
    Zengmin Xu
    Jinsong Wu
    Lixian Sun
    Haibin Jia
    [J]. Visual Intelligence, 2 (1):
  • [9] Development of a machine vision system: real-time fabric defect detection and classification with neural networks
    Celik, H. I.
    Dulger, L. U.
    Topalbekiroglu, M.
    [J]. JOURNAL OF THE TEXTILE INSTITUTE, 2014, 105 (06) : 575 - 585
  • [10] A real-time and accurate convolutional neural network for fabric defect detection
    Li, Xueshen
    Zhu, Yong
    [J]. COMPLEX & INTELLIGENT SYSTEMS, 2024, 10 (03) : 3371 - 3387