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Object Recognition Based Smart Digital Processing Using Fuzzy Logic

Guddi Singh1

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-11 , Page no. 42-44, May-2019

Online published on Jun 15, 2019

Copyright © Guddi Singh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Guddi Singh, “Object Recognition Based Smart Digital Processing Using Fuzzy Logic,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.11, pp.42-44, 2019.

MLA Style Citation: Guddi Singh "Object Recognition Based Smart Digital Processing Using Fuzzy Logic." International Journal of Computer Sciences and Engineering 07.11 (2019): 42-44.

APA Style Citation: Guddi Singh, (2019). Object Recognition Based Smart Digital Processing Using Fuzzy Logic. International Journal of Computer Sciences and Engineering, 07(11), 42-44.

BibTex Style Citation:
@article{Singh_2019,
author = {Guddi Singh},
title = {Object Recognition Based Smart Digital Processing Using Fuzzy Logic},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {11},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {42-44},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1009},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=1009
TI - Object Recognition Based Smart Digital Processing Using Fuzzy Logic
T2 - International Journal of Computer Sciences and Engineering
AU - Guddi Singh
PY - 2019
DA - 2019/06/15
PB - IJCSE, Indore, INDIA
SP - 42-44
IS - 11
VL - 07
SN - 2347-2693
ER -

           

Abstract

Object recognition can be viewed as a part of a computer vision system in which the image patterns will be converted into a feature space and in turn this will be transformed into the classification of various objects to be identified. Object recognition requires a prior knowledge of the object description. Typically these descriptions include shape, texture, color, and size of the occurrence of such objects in an image. For identifying image different approaches are followed such as similarity based approach and discontinuity approach. Since these approaches does not give better results hence we have applied Fuzzy logic-K means for identifying different objects in an image. The model accuracy is tested on MATLAB.

Key-Words / Index Term

Object recognition, Fuzzy Logic, K means, Digital Image, Cluster

References

[1] Tiu Lin and Edwin, Digital Image processing Using Matlab 3rd Edition, 2016.
[2] Abhimanyu, "Computational strategies for object recognition," ACM Computing Surveys, vol. 34, No.1, March 2017.
[3] Linder Swapnil," Theory of edge detection," Proc. of Royal Soc. London B. 207, pp.187-217, 2014.
[4] Yasir Meri, Pattern Recognition with fuzzy objective function algorithms, Plenum Press, NY, 2015.
[5] Anil Kumar and Sanjeev Pathak, Fuzzy models for graph recognition, JIER, 2017.