Provides an optimization system for controlling input and output of materials in large industrial depots using the combination of image processing and RFID

  • Khaled Alidoost Islamic Azad University of Lamerd
Keywords: Material input and output System, Large Industrial Storage, Image Processing and RFID

Abstract

The purpose of this research is to provide an optimization system for controlling the input and output of material (goods) in large industrial depots using the
combination of image processing and RFID. One of the practical applications of information technology in the industrial domain, and in particular intelligent
systems, is intelligent detection systems that control the exit of objects from the warehouse, which has many uses in order to mechanize the processes required to identify objects. Image processing and the system for detecting goods leaving the warehouse and detecting radio waves or RFIDs due to their proper  capabilities and the use of new technologies have a special place in intelligent material identification systems. Of course, along with the unique features of the above methods, each one has some irrefutable disadvantages. In this project, we tried to provide a combination of advantages of two methods of intelligent identification of objects in industrial warehouses such as RFID and image processing, which, with  the elimination of the disadvantages of the two methods, has a higher accuracy than each method.

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Author Biography

Khaled Alidoost, Islamic Azad University of Lamerd

Computer Engineering,

References

-Albright,B.” Frontline Solutions”, Goals for implementing RFID include inventory management
and quality control improvements. Sep 1, 2005.Avaliable
in: http://www.innovateforum.com/innovate/Manufacturing/Rockwell-Testing-RFID-to-TrackInventory/ArticleStandard/Article/detail/177379
- Chia-Feng Juang, Guo-Cyuan Chen, Chung-Wei Liang, Demei Lee, "Stereo-camera-based
object detection using fuzzy color histograms and a fuzzy classifier with depth and shape
estimations", Applied Soft Computing, Volume 46, 2016, PP. 753–766.
-Deepti Bhagwani, "OBJECT DETECTION AND REORGANIZATION BY IMAGE PARSING
USING WAVELET TECHNIQUE", Journal of Computer Studies and Research (ISTP-JCSR),
Volume 1, Issue 1, 2013, PP. 1 -5.
- Esther Antúnez, Rebeca Marfil, Juan P. Bandera, Antonio Bandera, "Part-based object
detection into a hierarchy of image segmentations combining color and topology", Pattern
Recognition Letters, Volume 34, Issue 7, 2013, PP. 744–753.
-Gong Cheng, Junwei Han, "A survey on object detection in optical remote sensing images",
ISPRS Journal of Photogrammetry and Remote Sensing, Volume 117, 2016, PP. 11 –28.
- Goldman, Mahmood,(2006), Supply Chain Management. Electronic Education WIS in Shiraz
University. Section 7 (RFID). Shiraz University Press
Hicks D.A.,‘A four step methodology for using simulation and optimizationtechnologies in
strategic supply chain planning’, Proceedings of the 1999 Winter Simulation Conference,pp
1215-1220
-Jin-Gang Yu, Gui-Song Xia, Jianjin Deng, Jinwen Tian, "Small object detection in forwardlooking infrared images with sea clutter using context-driven Bayesian saliency model", Infrared
Physics & Technology, Volume 73, 2015, PP. 175–183.
- Jamshidi, Behnam and Alireza Dehghan, 2007, The Ways of Using Information Technology in
New Storage, The First International Conference on Supply Chain Management and Information
Systems, Iranian Strategic Management Association, http://www.civilica.com/Paper-SCMIS01 -
SCMIS01_018.html
- Kiani, Arman, Mohammadian Roshan, Yasser, (2005), Intelligent Image Processing and
Optimization of Convolution Methods Using Fuzzy Systems, 8th Student Conference on
Electrical Engineering, Kerman, Shahid Bahonar University of Kerman,
http://www.civilica.com/Paper -ISCEE08-ISCEE08_209.html
- Rezapour, Taha Yasin and Mehregan, Mahdavi, (2011), Application of Information
Technology in New Stocks, The First National Conference on Computer and Information
Technology Students, Tabriz, Tabriz University, http://www.civilica.com/Paper-CSCCIT01 -
CSCCIT01_052. html
-Rahebi, J. Elmi, Z. Farzam nia, A. Shayan, K. (2010). Digital Image Edge Detection Using an
Ant Colony Optimization Based on Genetic Algorithm. 978-1-4244-6502-6/10/$26.00_c 2010
IEEE.
- Singh, K. K. Bajpai, M. K. Pandey, R. K., " A NOVEL APPROACH FOR EDGE
DETECTION OF LOW CONTRAST SATELLITE IMAGES", The International Archives of
the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-3/W2,
2015.
- Shemirani, Ali, (2006), 26th Monthly Journal of the Telecommunication, April, and
Technology Highway Weekly, April 2006
-Yogesh V, J (2002). Information Visibility and Its Effect on Supply Chain Dynamics. Submitted
to the Department of Mechanical Engineering, Indian Institute of Technology, Bombay, India
-Yali Li, Shengjin Wang, Qi Tian, Xiaoqing Ding, "Feature representation for statisticallearning-based object detection: a review", Pattern Recognition, Volume 48, Issue 11 , 2015, PP.
3542–3559.
- Zarif, Pooyan ,(2006), Handling technology to RFID technology
- Zarezadeh, Maryam, and Madani, Mohsen, (1394), An Improved Algorithm for Locating
Antenna Readers for Warehouse Antenna Using RFID Technology, Second International
Conference on Electrical Engineering and Computer Science, Shiraz, International Millennium
Development Project Campus, http: // www.
Published
2018-01-31
How to Cite
Alidoost, K. (2018). Provides an optimization system for controlling input and output of materials in large industrial depots using the combination of image processing and RFID. IJRDO -Journal of Computer Science Engineering, 4(1), 01-26. https://doi.org/10.53555/cse.v4i1.1835