Imageprocessing based pincode recognizing and sectionwise courier sorting system

International Journal of Electrical and Electronics Engineering
© 2016 by SSRG - IJEEE Journal
Volume 3 Issue 3
Year of Publication : 2016
Authors : Piyush Kiran Redgaonkar, Ajinkya Prakash Sonar, Amit Sunil Tatar, R. Bhambhare
How to Cite?

Piyush Kiran Redgaonkar, Ajinkya Prakash Sonar, Amit Sunil Tatar, R. Bhambhare, "Imageprocessing based pincode recognizing and sectionwise courier sorting system," SSRG International Journal of Electrical and Electronics Engineering, vol. 3,  no. 3, pp. 16-18, 2016. Crossref,


In India, post and courier system are one of the most commonly used communication portals. The Indian postal system is the biggest network among whole world. In India the people living in the rural area are more as compared to the metropolitan region. Due to such circumstances a system should be developed which is efficient to handle large number of posts and parcels at post courier stations. For such purpose, we are designing a system which will eliminate all possibilities of the errors produced by traditional sorting methodologies. We are implementing the system with the help of LabVIEW software which uses the Optical Character Recognition (OCR) technique to recognize the address. On the input side camera is used as a detector to capture images of the envelope. While using the Optical Character Recognition technique the detection of the address can be done without compulsion of pin code. LabVIEW will compare the input image with the stored database and as it matches with stored database, a moving arm will take the parcel to its appropriate locations. This, all process will minimize human errors and the number of other error probabilities caused due to conventional system.




[1] Mani, Nallasamy, Srinivasan, B., "Application of artificial neural network model for optical character recognition," Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on , vol.3, no., pp.2517,2520 vol.3, 12-15 Oct 1997, doi: 10.1109/ICSMC.1997.635312.
[2] Mi-Ae Ko, Young-Mo Kim, "A simple OCR method from strong perspective view," Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on , vol., no., pp.235,240, 13-15 Oct. 2004, doi: 10.1109/AIPR.2004.8.
[3] Kabir, E., Downton, A.C., Birch, R., "Recognition and verification of postcodes in handwritten and hand-printed addresses," Pattern Recognition, 1990. Proceedings. 10th International Conference on , vol.i, no., pp.469,473 vol.1, 16- 21 Jun 1990, doi: 10.1109/ICPR.1990.118148
[4] Ahmadi, A., Ritonga, M.A., Abedin, M.A., Mattausch, H.J., Koide, T., "A Learning OCR System Using Short/Long-term Memory Approach and Hardware Implementation in FPGA," Evolutionary Computation, 2006. CEC 2006. IEEE Congress on , vol., no., pp.687,693, 0-0 0, doi: 10.1109/CEC.2006.1688378
[5] Cannon, M., Fugate, M., Hush, D.R., Scovel, C., "Selecting a restoration technique to minimize OCR error," Neural Networks, IEEE Transactions on , vol.14, no.3, pp.478,490, May 2003, doi: 10.1109/TNN.2003.811711
[6] Alon, Jonathan, Athitsos, V., Sclaroff, S., "Online and offline character recognition using alignment to prototypes," Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on , vol., no., pp.839,843 Vol. 2, 29 Aug.-1 Sept. 2005, doi: 10.1109/ICDAR.2005.177
[7] Kavallieratou, E., Stamatatos, S., Antonopoulou, H., "Machine-printed from handwritten text discrimination," Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on , vol., no., pp.312,316, 26- 29 Oct. 2004, doi: 10.1109/IWFHR.2004.65