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Reseach Article

Recognition of Bolt and Nut using Principle Component analysis

Published on November 2013 by A. S. Khobragade, Amol. I. Dhenge
2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
Foundation of Computer Science USA
NCIPET - Number 1
November 2013
Authors: A. S. Khobragade, Amol. I. Dhenge
0f0d6485-345b-4ad5-a9c6-d15100b42cf9

A. S. Khobragade, Amol. I. Dhenge . Recognition of Bolt and Nut using Principle Component analysis. 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013). NCIPET, 1 (November 2013), 0-0.

@article{
author = { A. S. Khobragade, Amol. I. Dhenge },
title = { Recognition of Bolt and Nut using Principle Component analysis },
journal = { 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013) },
issue_date = { November 2013 },
volume = { NCIPET },
number = { 1 },
month = { November },
year = { 2013 },
issn = 2249-0868,
pages = { 0-0 },
numpages = 1,
url = { /proceedings/ncipet/number1/551-1328/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%A A. S. Khobragade
%A Amol. I. Dhenge
%T Recognition of Bolt and Nut using Principle Component analysis
%J 2nd National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2013)
%@ 2249-0868
%V NCIPET
%N 1
%P 0-0
%D 2013
%I International Journal of Applied Information Systems
Abstract

The main aim of this paper is to build a method for recognition of bolt and nut which can be useful in mechanical industries. The objective of this study is to develop the image processing algorithm using principle component analysis to get the normalized resize images which would be suitable inputs for processing and detection. The Matlab software version 2011a is used to integrate all algorithms. This implementation also justify a prototype that emulates the sorting of nuts and bolts. The input is image through the high performance camera which is pre-processed at the suitable level. The image is then applied the principle component analysis (PCA) for the feature extraction. The resultant is given to the artificial neural network (ANN) system can detect object accurately and them accordingly as required for the application.

References
  1. Akbar H. and Prabuwono A. S. , "The design and development of automated visual inspection system for press part sorting," in Proc. International Conference on Computer Science and Information Technology (ICCSIT'08), 2008, pp. 683-686.
  2. Akbar H. and Prabuwono A. S. , "Webcam based system for press part industrial inspection," International Journal of Computer Science and Network Security, vol. 8, pp. 170-177, Oct. 2008.
  3. Akbar H. , Prabuwono A. S. , Izzah Z. , and Tahir Z. , "Image processing algorithm in machine vision approach for industrial inspection," in Proc. the 1st Makassar International Conference on Electrical Engineering and Informatics (MICEEI'08), 2008, pp. 58-62.
  4. Akbar H. and Prabuwono A. S. , "Automated visual inspection (AVI) research for quality control in metal stamping manufacturing," in Proc. the 4th International Conference on Information Technology and Multimedia (ICIMU'08), 2008, pp. 626-630.
  5. Dewanto S. , Suwandi, T. and Yanto, E. , "Sistem sortir mur dan baut menggunakan jaringan syaraf tiruan," Jurnal Teknik Komputer, vol. 13, no. 1, pp. 1-13, 2005.
  6. Kyaw M. M. , Ahmed S. K. , and Md Sharrif Z. A. , "Shape-based sorting of agricultural product using support vector machines in a MATLAB/SIMULINK environment," in Proc. 5th International Colloquium on Signal Processing & Its Applictions (CSPA'09), 2009, pp. 135-139.
  7. Zhao Z. , Xin H. , Ren Y. , and Guo X. , "Application and comparison of BP neural network algorithm in MATLAB," in Proc. International Conference on Measuring Technology and Mechantronic Automation, 2010, pp. 590-593.
  8. Lahajnar F. , Bernard R. , Pernus F. , and Kovacic S. , "Machine vision system for inspecting electric plates," Computers in Industry, vol. 47, no. 1, pp. 113-122, Jan. 2001.
  9. Liu L. , Chen J. , and Xu. L. , Realization and Application Research of BP neural network based on MATLAB, 2008.
  10. Nooritawati M. T. , Aini H. , Salina A. S. , and Hafizah H. , "Pengecaman insan berasaskan kaedah profil sentroid dan pengelas rangkaian neural buatan," Jurnal Teknologi Universiti Teknologi Malaysia, pp. 69-79, Sep. 2010.
  11. Prabuwono A. S. and Akbar H. , "PC based weight scale system with load cell for product inspection," in Proc. International Conference on Computer Engineering and Technology (ICCET'09), 2009, pp. 343-346.
  12. Prabuwono A. S. , Sulaiman R. , Hamdan A. R. , and Hasniaty A. , "Development of intelligent visual inspection system (IVIS) for bottling machine," in Proc. IEEE Region 10 Conference of TENCON, 2006, pp. 1-4.
  13. Saad H. and Hussain A. , "Classification for the ripeness of papayas using artificial neural network (ANN) and threshold rule," in Proc. 4th Student Conference Research and Development, 2006, pp. 132-136.
  14. Siang J. J. , Jaringan Syaraf Tiruan & Pemogramannya Menggunakan Matlab, Penerbit ANDI, Jogjakarta, 2005.
  15. A. S. Prabuwono, Y. Away, and A. R. Hamdan, Design and Development of Intelligent Vision System for Quality Control in Bottling Production Line, Proceeding of FTSM UKM Postgraduate Seminar, 2004, pp. 138-141.
  16. L. N. Wayne, The Automated Inspection of Moving Webs using Machine Vision, IEE Colloquium in Application of Machine Vision, 1995, pp. 3/1-3/8.
  17. " Recognition of Bolt and Nut using Stationary Wavelet Transform"Ambarish Salodkar, M. M. Khanapurkar. International Conference on Emerging Frontiers in Technology for Rural Area (EFITRA) 2012 Proceedings published in International Journal of Computer Applications® (IJCA)
Index Terms

Computer Science
Information Sciences

Keywords

Pattern recognition bolt and nut principle component analysis (PCA) artificial neural network.