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Camera Based Product Counting of Belt Conveyors

Year 2014, Volume: 4 Issue: 2, 771 - 785, 01.12.2014

Abstract

This work involves the development of a vision-based system for counting the number of products that pass on a conveyor belt. The system has applications in automatic control and optimization of industrial processes that involve belt conveyors and their related packaging operations. Determining automatically the number of products to be packaged without the need for additional hardware setup yields an important reducement in the initial cost of the complete installation. In this work, by introducing a vision based approach, thus with involvement of image and video processing techniques, counting of products passing on a belt conveyor system just using a camera is investigated.

References

  • R. C. Gonzalez and R. E. Woods, “Digital Image Processing”. Gatesmark Publishing, 2008.
  • R. C. Gonzalez, R. E. Woods, and S. Eddins, “Digital Image Processing UsingMatlab”. Gatesmark Publishing , 2009.
  • J. J. Ding, S. C. Pei, J. D. Huang, G. C. Guo, Y. C. Lin, N. C. Shen, and Y. S. Zhang,“Short response Hilbert transform for edge detection,” CVGIP, 2007.
  • S. C. Pei and J. J. Ding, “Improved Harris’ algorithm for corner and edge detections,” ICIP 2007.
  • Thabit Sultan Mohammed and Nidal Ibrahim al-Tataie, “Artificial Neural Network as a Decision- Makers for Stereo Matching”, GSTF- International Journal on ComputingVol. 1, No. 3, pp (89 – 94), August 2011.
  • T.H. Lee, “Edge Detection Analysis”, National Taiwan University, technical report 2008.
  • J. Canny, “Finding Edges and Lines in Images,” Massachusetts Institute of Technology, Cambridge, Massachusetts, USA, Tech. Rep. no. 720, 1983.
  • R. Makkar, “Study of Image Matching Techniques”, M.Sc. Thesis, Punjabi University, 2008.
  • V. N. Radhika, B. Katikeyan, “Robust Stereo Image Matching for Space borne Imagery”, IEEE Transactions on geosciences and remote sensing, vol. 45, No. 9, Sep. 2007.
  • Thabit Sultan Mohammed, Nedhal Ibrahim Al-Taie, “Applying a Neural Network Framework for Stereo Matching”, Annual Int. Conf. on Control, Automation and Robotics (CAR 2011), Singapore - 2011.
  • Z. Guoqing, Y. Bao~onga nd T. Xiaofaiig, “A Software Package of Stereo Vision”, ICSP ‘ 1996.
  • D. Anastasia and Y. Andreopoulos, “Software Designs of Image Processing Tasks with Incremental Refinement of Computation”, Signal Processing Systems, 2009. SiPS 2009.
  • Wim Abbeloos. Fast matlab stereo matching algorithm (sad). Master’s thesis, sep 2010.
  • Jean-Yves Bouguet. Camera calibration toolbox for matlab. Technical report, California Institute of Technology, jul 2010.
  • Gary Bradski and Adrian Kaehler. Learning OpenCV. O’Reilly Media, 1st edition, 2008. ISBN 978-0-596- 51613-0.
  • Edward R. Dougherty and Roberto A. Lotufo. Hands-on Morphological Image Processing. SPIE Press, 1st edition, 2003. ISBN 0-8194-4720-X.
  • Rafael C. Gonzalez and Richard E. Woods. Digital Image Processing. Pearson Education, 3rd edition, 2008. ISBN 978-0-13-505267-9.
  • Stefano Mattoccia. Stereo vision: Algorithms and applications. Technical report, University of Bologna, feb 2011.
  • Ayache, N., and Faugeras,O. (1986). “HYPER: A new aproach for the recognition and positioning of two-dimensional objects.” IEEE Trans. Pattern Anal PAMI 8 (1B Press.
  • Bolles, R. C., and Horaud, P. (1986). “A three-dimensional part orientation system.” Int.J.Rob. Res. 5(3): 3-26.
  • Brooks, R. A. (1981). “Symbolic reasoning among 3-D models and 2-D images. .” Artif Intell 17: 285-348.
  • Brooks, R. A. (1983). “Model- based three dimensional interpertations of twodimensional imIEEE Trans. Pattern Anal PAMI 5(2): 140-150.
  • Duda, R. O., aages.” Forsyth, D. A., and Ponce J. (2003). Computer Vision A modern Approach Edition. London, PrentiHall. F ): 44-54.
  • Ellman, R., and Dreyfus, S. (1962). Applied dynamic programming . Princeton, Princeton University
  • Hanson, A.J. (1991). “An optimization framework fro feature extraction.” Mach, Vision Appl 4: 59-87.
  • Kimme, C., Ballard, D., and Sklansky, J. (1975). “Finding circles by an array of accumulators.” Communications of the ACM 18(2): 120-122.
  • Mathworks (1998). RGB Images. http://visl.technion.ac.il/labs/ anat//2ImageTypes/#RGB%20 Images.
  • Nölle, M., Jonsson, B., and Rubik, M. (2004). Coin Images Seibersdorf- Benchmark, ARC Seibersdorf research GmbH: 1-8. Provine, J.,
  • McClintock,M. , Murray, K., and Chau, A. . (1999). “Automatic coin counter.”
  • Rosenfeld, A. (1969). Picture Processing by Computer. New York, Academic Press.
  • Sonka, M., Hlavac,v., and Boyle, R. (1999). Image processing, analysis and machine vision. Londow, PWS.
  • Suetens, P., Fua, P., and Hanson, A. J. (1992). “Computational strategies for object recognition.” ACM Computing Surveys 24(1): 5-61.
  • Tenenbaum, J. M., and Barrow, H.G. (1977). “Experiments in interpretation-guided segmentation.” Artif. Intell 8: 241-274.
  • Zhao, W., Chellappa, R., Phillips, P.J., and Rosenfeld, A. (2003). “Face recognition: a literature survey.” ACM Computing Surveys 35(4): 399- 458.
  • J. Koenderik. The structure of images. Biol. Cybern, 50:363–370, 1984.
  • O. Carlsson L. Nyberg and B. Schmidtbauer. Estimation of the size distribution of fragmented rock in ore mining through automatic image processing. In Technological and Methodological Advances in Measurement - Acta IMEKO 1982, volume 3 of Data processing and System aspects, pages 293–302, Berlin, West Germany, May 1983. North Holland Publishing Company.
  • G. Von Borries L. Yachner, C. Gonzales and R. Nobile. Coarse particle size distribution analyzer. In IFAC Symposium on Automation for Mineral Resource Development, Brisbane Queensland, Australia, July 1985.
  • T.B. Lange. Measurement of the size distribution of rocks on a conveyor belt using machine vision. PhD thesis, University of Witwatersrand, Faculty of Engineering, University of Witwatersrand, Johannesburg, 1990.
  • N.H. Maerz. Image sampling techniques and requirements for automated image analysis of rock fragmentation. Proceedings of the FRAGBLAST 5, Workshop on Measurement of blast fragmentation, pages 115–120, August 1996.
  • N.H. Maerz. Reconstructing 3-d block size distributions from 2-d measurements on sections. Proceedings of the FRAGBLAST 5, Workshop on Measurement of Blast Fragmentation, pages 39–43, August 1996.
  • N.H. Maerz. Aggregate sizing and shape determination using digital image processing. Center for Aggregates Research (ICAR) Sixth Annual Symposium Proceedings, pages 195– 203, 1998.
  • N.H. Maerz and T.C. Palangio. Wipfrag system ii- online fragmentation analysis. FRAGBLAST 6, Sixth Internation Symposium for rock fragmentation by blasting, pages 111–115, August 1999.
  • N.H. Maerz and W. Zhou. Optical digital fragmentation measuring systems-inherent sources of error. FRAGBLAST, The international journal for blasting and fragmentation, 2(4):415–431, 1998.
  • N.H. Maerz andW. Zhou. Calibration of optical digital fragmentation measuring systems. FRAGBLAST, The international journal for blasting and rock fragmentation, 4(2):126– 138, 2000.
  • D.J. Mashao. Comparing svm and gmm on parametric feature-sets. Proceedings of the 14th Annual Symposium of the Pattern Recognition Association of South Africa, 2003.
  • C. McDermott and N.J. Miles. The measurement of rock fragmentation using image analysis. Departmental magazine, Department of Mining Engineering, pages 49–61, 1988.
  • D.H. Marimont M.J. Black, G. Sapiro and D. Heeger. Robust anisotropic diffusion. IEEE Transactions on Image Processing, 7(3):421–232, March 1998.
  • S.G. Mkwelo. A comparative evaluation of evolutionary design methods in engineering. A 4th year undergraduate thesis in the department of electrical engineering, University of Cape Town, October 2001.
  • T.J. Napier-Munn. An introduction to comparative statistics and experimental design for Minerals Engineers. Julius Kruttschnitt mineral research centre, The University of Queensland, 2 edition, 2001.
  • T.C. Palangio N.H. Maerz and J.A. Franklin. Wipfrag image based granulometry system. Proceedings of the FRAGBLAST 5, Workshop on measurement of Blast Fragmentation, pages 91–99, August 1996.
  • T.C. Palangio and N.H. Maerz. Case studies using the wipfrag image analysis system. FRAGBLAST 6, Sixth Symposium for rock fragmentation by blasting, pages 117–120, August 1999.
  • P. Perona and J. Malik. Scale- space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(7):629 – 639, July 1990.
  • T. Poggio and S. Smale. The mathematics of learning: Dealing with data. Notices of the AMS, 50(5), 2003.
  • C. Pretorious and A.L. Nel. Rock size mintoring on conveyor belt systemsusing neural networks. Proceedings of the second South African Workshop on Pattern Recognition, pages 100–110, November 1991.
  • W. Hue Q. Song and W. Xie. Robust support vector machine with bullet hole image classification. IEEE Transactions on Systems, Man, and Cybernetics-Part C, 32(4):440– 448, November 2002.
  • J.B.T.M. Roerdink and A. Meijster. The watershed transform: Definitions, algorithms and parallelization strategies. Fundamenta Informaticae, pages 187–228, 2000.
  • G. de Jager S. Mkwelo and F. Nicolls. Watershed-based segmentation of rock-scenes and proximity-based classification of watershed regions under uncontrolled lighting conditions. Proceedings of the 14th Annual Symposium of the Pattern Recognition Association of South Afrca, 2003.
  • J. Serra. Image analysis and mathematical morphology, volume 1. Academic Press, 1982.
  • C. Tomasi and R. Manduchi. Bilateral filtering for gray and color images. Proceedings of the International Conference on Computer Vision, 1998.
  • R. van den Boomgard and J. van den Weijer. On the equivalence of local-mode finding, robust estimation and mean-shift analysis as used in early vision tasks. Proceedings of the 16th International Conference on Pattern Recognition, 3:927–930, 2002.
  • L. Vincent and P. Soille. Watersheds in digital spaces: an effiecient algorithm based on immersion simulations. PAMI, 13(6):583–598, 1991.
  • The Webmaster. The split-engineering website, February 2004. www. spliteng.com.
  • The Webmaster. The wipfrag website, March 2004. www.wipware.com.
  • David Wigeson. Fragmentation analysis using computer vision techniques. Master’s thesis, University of Witwatersrand, 1987.
  • B.A. Willis. Mineral Processing technology. Butterworth Heinenmann publishing (Ltd), 6 edition, 1997.
  • A. Witkin. Scale-space filtering. Int. Joint Conf. Artificial Intelligence, pages 1019– 1021, 1983.
  • B.A Wright. The development of a vision based flotation froth analysis system. Master’s thesis, University of Cape Town, Faculty of Engineering and Built Environment, University of Cape Town, Rondebosch 7700, South Africa, 1999.
Year 2014, Volume: 4 Issue: 2, 771 - 785, 01.12.2014

Abstract

References

  • R. C. Gonzalez and R. E. Woods, “Digital Image Processing”. Gatesmark Publishing, 2008.
  • R. C. Gonzalez, R. E. Woods, and S. Eddins, “Digital Image Processing UsingMatlab”. Gatesmark Publishing , 2009.
  • J. J. Ding, S. C. Pei, J. D. Huang, G. C. Guo, Y. C. Lin, N. C. Shen, and Y. S. Zhang,“Short response Hilbert transform for edge detection,” CVGIP, 2007.
  • S. C. Pei and J. J. Ding, “Improved Harris’ algorithm for corner and edge detections,” ICIP 2007.
  • Thabit Sultan Mohammed and Nidal Ibrahim al-Tataie, “Artificial Neural Network as a Decision- Makers for Stereo Matching”, GSTF- International Journal on ComputingVol. 1, No. 3, pp (89 – 94), August 2011.
  • T.H. Lee, “Edge Detection Analysis”, National Taiwan University, technical report 2008.
  • J. Canny, “Finding Edges and Lines in Images,” Massachusetts Institute of Technology, Cambridge, Massachusetts, USA, Tech. Rep. no. 720, 1983.
  • R. Makkar, “Study of Image Matching Techniques”, M.Sc. Thesis, Punjabi University, 2008.
  • V. N. Radhika, B. Katikeyan, “Robust Stereo Image Matching for Space borne Imagery”, IEEE Transactions on geosciences and remote sensing, vol. 45, No. 9, Sep. 2007.
  • Thabit Sultan Mohammed, Nedhal Ibrahim Al-Taie, “Applying a Neural Network Framework for Stereo Matching”, Annual Int. Conf. on Control, Automation and Robotics (CAR 2011), Singapore - 2011.
  • Z. Guoqing, Y. Bao~onga nd T. Xiaofaiig, “A Software Package of Stereo Vision”, ICSP ‘ 1996.
  • D. Anastasia and Y. Andreopoulos, “Software Designs of Image Processing Tasks with Incremental Refinement of Computation”, Signal Processing Systems, 2009. SiPS 2009.
  • Wim Abbeloos. Fast matlab stereo matching algorithm (sad). Master’s thesis, sep 2010.
  • Jean-Yves Bouguet. Camera calibration toolbox for matlab. Technical report, California Institute of Technology, jul 2010.
  • Gary Bradski and Adrian Kaehler. Learning OpenCV. O’Reilly Media, 1st edition, 2008. ISBN 978-0-596- 51613-0.
  • Edward R. Dougherty and Roberto A. Lotufo. Hands-on Morphological Image Processing. SPIE Press, 1st edition, 2003. ISBN 0-8194-4720-X.
  • Rafael C. Gonzalez and Richard E. Woods. Digital Image Processing. Pearson Education, 3rd edition, 2008. ISBN 978-0-13-505267-9.
  • Stefano Mattoccia. Stereo vision: Algorithms and applications. Technical report, University of Bologna, feb 2011.
  • Ayache, N., and Faugeras,O. (1986). “HYPER: A new aproach for the recognition and positioning of two-dimensional objects.” IEEE Trans. Pattern Anal PAMI 8 (1B Press.
  • Bolles, R. C., and Horaud, P. (1986). “A three-dimensional part orientation system.” Int.J.Rob. Res. 5(3): 3-26.
  • Brooks, R. A. (1981). “Symbolic reasoning among 3-D models and 2-D images. .” Artif Intell 17: 285-348.
  • Brooks, R. A. (1983). “Model- based three dimensional interpertations of twodimensional imIEEE Trans. Pattern Anal PAMI 5(2): 140-150.
  • Duda, R. O., aages.” Forsyth, D. A., and Ponce J. (2003). Computer Vision A modern Approach Edition. London, PrentiHall. F ): 44-54.
  • Ellman, R., and Dreyfus, S. (1962). Applied dynamic programming . Princeton, Princeton University
  • Hanson, A.J. (1991). “An optimization framework fro feature extraction.” Mach, Vision Appl 4: 59-87.
  • Kimme, C., Ballard, D., and Sklansky, J. (1975). “Finding circles by an array of accumulators.” Communications of the ACM 18(2): 120-122.
  • Mathworks (1998). RGB Images. http://visl.technion.ac.il/labs/ anat//2ImageTypes/#RGB%20 Images.
  • Nölle, M., Jonsson, B., and Rubik, M. (2004). Coin Images Seibersdorf- Benchmark, ARC Seibersdorf research GmbH: 1-8. Provine, J.,
  • McClintock,M. , Murray, K., and Chau, A. . (1999). “Automatic coin counter.”
  • Rosenfeld, A. (1969). Picture Processing by Computer. New York, Academic Press.
  • Sonka, M., Hlavac,v., and Boyle, R. (1999). Image processing, analysis and machine vision. Londow, PWS.
  • Suetens, P., Fua, P., and Hanson, A. J. (1992). “Computational strategies for object recognition.” ACM Computing Surveys 24(1): 5-61.
  • Tenenbaum, J. M., and Barrow, H.G. (1977). “Experiments in interpretation-guided segmentation.” Artif. Intell 8: 241-274.
  • Zhao, W., Chellappa, R., Phillips, P.J., and Rosenfeld, A. (2003). “Face recognition: a literature survey.” ACM Computing Surveys 35(4): 399- 458.
  • J. Koenderik. The structure of images. Biol. Cybern, 50:363–370, 1984.
  • O. Carlsson L. Nyberg and B. Schmidtbauer. Estimation of the size distribution of fragmented rock in ore mining through automatic image processing. In Technological and Methodological Advances in Measurement - Acta IMEKO 1982, volume 3 of Data processing and System aspects, pages 293–302, Berlin, West Germany, May 1983. North Holland Publishing Company.
  • G. Von Borries L. Yachner, C. Gonzales and R. Nobile. Coarse particle size distribution analyzer. In IFAC Symposium on Automation for Mineral Resource Development, Brisbane Queensland, Australia, July 1985.
  • T.B. Lange. Measurement of the size distribution of rocks on a conveyor belt using machine vision. PhD thesis, University of Witwatersrand, Faculty of Engineering, University of Witwatersrand, Johannesburg, 1990.
  • N.H. Maerz. Image sampling techniques and requirements for automated image analysis of rock fragmentation. Proceedings of the FRAGBLAST 5, Workshop on Measurement of blast fragmentation, pages 115–120, August 1996.
  • N.H. Maerz. Reconstructing 3-d block size distributions from 2-d measurements on sections. Proceedings of the FRAGBLAST 5, Workshop on Measurement of Blast Fragmentation, pages 39–43, August 1996.
  • N.H. Maerz. Aggregate sizing and shape determination using digital image processing. Center for Aggregates Research (ICAR) Sixth Annual Symposium Proceedings, pages 195– 203, 1998.
  • N.H. Maerz and T.C. Palangio. Wipfrag system ii- online fragmentation analysis. FRAGBLAST 6, Sixth Internation Symposium for rock fragmentation by blasting, pages 111–115, August 1999.
  • N.H. Maerz and W. Zhou. Optical digital fragmentation measuring systems-inherent sources of error. FRAGBLAST, The international journal for blasting and fragmentation, 2(4):415–431, 1998.
  • N.H. Maerz andW. Zhou. Calibration of optical digital fragmentation measuring systems. FRAGBLAST, The international journal for blasting and rock fragmentation, 4(2):126– 138, 2000.
  • D.J. Mashao. Comparing svm and gmm on parametric feature-sets. Proceedings of the 14th Annual Symposium of the Pattern Recognition Association of South Africa, 2003.
  • C. McDermott and N.J. Miles. The measurement of rock fragmentation using image analysis. Departmental magazine, Department of Mining Engineering, pages 49–61, 1988.
  • D.H. Marimont M.J. Black, G. Sapiro and D. Heeger. Robust anisotropic diffusion. IEEE Transactions on Image Processing, 7(3):421–232, March 1998.
  • S.G. Mkwelo. A comparative evaluation of evolutionary design methods in engineering. A 4th year undergraduate thesis in the department of electrical engineering, University of Cape Town, October 2001.
  • T.J. Napier-Munn. An introduction to comparative statistics and experimental design for Minerals Engineers. Julius Kruttschnitt mineral research centre, The University of Queensland, 2 edition, 2001.
  • T.C. Palangio N.H. Maerz and J.A. Franklin. Wipfrag image based granulometry system. Proceedings of the FRAGBLAST 5, Workshop on measurement of Blast Fragmentation, pages 91–99, August 1996.
  • T.C. Palangio and N.H. Maerz. Case studies using the wipfrag image analysis system. FRAGBLAST 6, Sixth Symposium for rock fragmentation by blasting, pages 117–120, August 1999.
  • P. Perona and J. Malik. Scale- space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(7):629 – 639, July 1990.
  • T. Poggio and S. Smale. The mathematics of learning: Dealing with data. Notices of the AMS, 50(5), 2003.
  • C. Pretorious and A.L. Nel. Rock size mintoring on conveyor belt systemsusing neural networks. Proceedings of the second South African Workshop on Pattern Recognition, pages 100–110, November 1991.
  • W. Hue Q. Song and W. Xie. Robust support vector machine with bullet hole image classification. IEEE Transactions on Systems, Man, and Cybernetics-Part C, 32(4):440– 448, November 2002.
  • J.B.T.M. Roerdink and A. Meijster. The watershed transform: Definitions, algorithms and parallelization strategies. Fundamenta Informaticae, pages 187–228, 2000.
  • G. de Jager S. Mkwelo and F. Nicolls. Watershed-based segmentation of rock-scenes and proximity-based classification of watershed regions under uncontrolled lighting conditions. Proceedings of the 14th Annual Symposium of the Pattern Recognition Association of South Afrca, 2003.
  • J. Serra. Image analysis and mathematical morphology, volume 1. Academic Press, 1982.
  • C. Tomasi and R. Manduchi. Bilateral filtering for gray and color images. Proceedings of the International Conference on Computer Vision, 1998.
  • R. van den Boomgard and J. van den Weijer. On the equivalence of local-mode finding, robust estimation and mean-shift analysis as used in early vision tasks. Proceedings of the 16th International Conference on Pattern Recognition, 3:927–930, 2002.
  • L. Vincent and P. Soille. Watersheds in digital spaces: an effiecient algorithm based on immersion simulations. PAMI, 13(6):583–598, 1991.
  • The Webmaster. The split-engineering website, February 2004. www. spliteng.com.
  • The Webmaster. The wipfrag website, March 2004. www.wipware.com.
  • David Wigeson. Fragmentation analysis using computer vision techniques. Master’s thesis, University of Witwatersrand, 1987.
  • B.A. Willis. Mineral Processing technology. Butterworth Heinenmann publishing (Ltd), 6 edition, 1997.
  • A. Witkin. Scale-space filtering. Int. Joint Conf. Artificial Intelligence, pages 1019– 1021, 1983.
  • B.A Wright. The development of a vision based flotation froth analysis system. Master’s thesis, University of Cape Town, Faculty of Engineering and Built Environment, University of Cape Town, Rondebosch 7700, South Africa, 1999.
There are 67 citations in total.

Details

Other ID JA68RK48RK
Journal Section Articles
Authors

M. Uğur Parlak This is me

Publication Date December 1, 2014
Published in Issue Year 2014 Volume: 4 Issue: 2

Cite

APA Parlak, M. U. (2014). Camera Based Product Counting of Belt Conveyors. International Journal of Electronics Mechanical and Mechatronics Engineering, 4(2), 771-785.