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Smart Veggie Identification and Alerting System for Supermarkets using Image Processing Techniques and Neural Networks

by Hewasinghe H. H. K, Pemarathne W. P. J
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 30
Year of Publication: 2018
Authors: Hewasinghe H. H. K, Pemarathne W. P. J
10.5120/ijca2018918185

Hewasinghe H. H. K, Pemarathne W. P. J . Smart Veggie Identification and Alerting System for Supermarkets using Image Processing Techniques and Neural Networks. International Journal of Computer Applications. 182, 30 ( Dec 2018), 1-5. DOI=10.5120/ijca2018918185

@article{ 10.5120/ijca2018918185,
author = { Hewasinghe H. H. K, Pemarathne W. P. J },
title = { Smart Veggie Identification and Alerting System for Supermarkets using Image Processing Techniques and Neural Networks },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2018 },
volume = { 182 },
number = { 30 },
month = { Dec },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number30/30215-2018918185/ },
doi = { 10.5120/ijca2018918185 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:12:53.045269+05:30
%A Hewasinghe H. H. K
%A Pemarathne W. P. J
%T Smart Veggie Identification and Alerting System for Supermarkets using Image Processing Techniques and Neural Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 30
%P 1-5
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The recent advances in the field of image processing has become a powerful quantitative method in development of science and engineering. Image recognition is one of the foremost areas in computer vision, it yields high degree understanding through computers, one of the maximum crucial regions in recognition is object recognition that's the process of locating a specific object in an image or video surveillance. This paper presents the current state of image processing techniques to identify vegetables and fruits and its capabilities to improve hardware resources with the growing demands of the business industry. The proposed system can identify vegetables and fruits in a basket that are to be retailed and alert the authorities when a basket is going to be finished. The application is based on color and size comparison of the vegetables and fruits in a live video with a reference image and there by extract similar features by using neural network for identification. Baskets are marked with a colored line to indicate the level of the item. Particular level is identified through color identification and notify the responsible parties.

References
  1. S. Sojitra and G. Patel, “A Review of Smart Shopping Systems,” 2016.
  2. R. M. Bolle, J. H. Connell, N. Haas, R. Mohan, and G. Taubin, “VeggieVision: a produce recognition system,” 1996, pp. 244–251.
  3. W. Applebaum, “studying customerbehaviorinretailstores-090623023217-phpapp01.”
  4. C. M. Sukanya, R. Gokul, and V. Paul, “A Survey on Object Recognition Methods,” Int. J. Sci. Eng. Comput. Technol., vol. 6, no. 1, p. 48, 2016.
  5. D. Lu, D. A. Kiewit, and J. Zhang, Market research method and system for collecting retail store and shopper market research data. Google Patents, 1994.
  6. Z. Ali, “RFID Based Smart Shopping and Billing,” 2013.
  7. I. B. Venkateswarlu, “Analytical Survey of Colour to Greyscale Conversion Methods Based on Primary Image Processing Techniques.” International Journal of Advanced Research in Computer Science and Software Engineering, 10-Oct-2014.
  8. A. Pandit and J. Rangole, “Literature Review On Object Counting Using Image Processing Techniques.” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 04-Apr-2014.
  9. A. Ushma and P. D. A. R. M. Shanavas, “Object Detection In Image Processing Using Edge Detection Techniques.” IOSR Journal of Engineering (IOSRJEN), Mar-2014.
  10. International Conference on Pattern Recognition, A. Sanfeliu, and International Association for Pattern Recognition, Eds., VARIOUS OBJECT RECOGNITION TECHNIQUES FOR COMPUTER VISION. Los Alamitos, Calif.: IEEE Computer Society, 2000.
  11. K. Khurana and R. Awasthi, “Techniques for object recognition in images and multi-object detection,” Int. J. Adv. Res. Comput. Eng. Technol. IJARCET, vol. 2, no. 4, pp. 1383–1388, 2013.
  12. L. G. Shapiro and G. C. Stockman, Computer vision. Upper Saddle River, NJ: Prentice Hall, 2001.
  13. A. Muhtaseb, S. Sarahneh, and H. Tamimi, “FruitVegetable_Recognition.” ReearchGate, 12-Feb-2015.
  14. “Image_Segmentation_and_Recognition_Using.” .
  15. D. Senthamaraikannan, S. Shriram, and J. William, “Real time color recognition,” Int. J. Innov. Res. Electr. Electron. Instrum. Control Eng., vol. 2, no. 3, 2014.
  16. R. Buksh, S. Routh, P. Mitra, S. Banik, A. Mallik, and S. D. Gupta, “MATLAB based image editing and color detection,” Int. J. Sci. Res. Publ., vol. 4, no. 1, pp. 1–6, 2014.
  17. B. R. Navada, K. V. Santhosh, S. Prajwal, and H. B. Shetty, “An image processing technique for color detection and distinguish patterns with similar color: An aid for color blind people,” 2014, pp. 333–336.
  18. M. Moghimi, “Using color for object recognition,” Calif. Inst. Technol. Tech Rep, 2011.
  19. Y. Hirano, C. Garcia, R. Sukthankar, and A. Hoogs, “Industry and object recognition: Applications, applied research and challenges,” in Toward Category-Level Object Recognition, Springer, 2006, pp. 49–64.
  20. K. Wilson, “Real- Time Tracking for Multiple Objects Based on Implementation of RGB Color Space in Video,” Int. J. Signal Process. Image Process. Pattern Recognit., vol. 9, no. 4, pp. 331–338, Apr. 2016.
Index Terms

Computer Science
Information Sciences

Keywords

Image processing Object recognition neural network Color identification Fruits and vegetable recognition

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