Advance Technological Approach for Maize Seed Variety Identification Using Image Processing

Authors

  • Satish Hakkalli  Lecturer, Department of Computer Science, Al khateeb Polytechnic Bhoopasandra, Bangalore, Karnataka, India
  • Varun C R  Lecturer, Department of Computer Science, Al khateeb Polytechnic Bhoopasandra, Bangalore, Karnataka, India
  • Pavankumar Naik  Assistant Professor, Department of Computer Science & Engineering, SKSVMACET, Karnataka, India

DOI:

https://doi.org/10.32628/CSEIT195521

Keywords:

Matlab, Tested seeds, Sample seed, Image Processing, Threshold

Abstract

In imaging science, image processing is processing of images using mathematical operations by using any form of signal processing for which the input is an image, a series of images, or a video, such as a photograph or video frame. Our approach is to make an automatic method for identifying different varieties of maize seed using Image processing technology. As we have different tools for image processing we have used MatLab for implementing the proposed system. By maintaining some standardization in your proposed system we prepared the dataset using different verities of maize seed images and These images are compared against the sample seed image (input image), if input image is same as one of the dataset image verity than your proposed system displays the seed is recognized as of respected variety.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-10-30

Issue

Volume 5, Issue 5, September-October-2019

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Satish Hakkalli, Varun C R, Pavankumar Naik, " Advance Technological Approach for Maize Seed Variety Identification Using Image Processing " International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 5, pp.106-111, September-October-2019. Available at doi : https://doi.org/10.32628/CSEIT195521