Rice Grain Grading Classification Based On Perimeter Using Moore-Neighbor Tracing Method

Authors

  • M.M. Piramli Optimization, Modeling, Analysis, Simulation and Scheduling (OptiMASS) Research Group, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Melaka, Malaysia.
  • A.F.N.A. Rahman Optimization, Modeling, Analysis, Simulation and Scheduling (OptiMASS) Research Group, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Melaka, Malaysia.
  • S.F. Abdullah Optimization, Modeling, Analysis, Simulation and Scheduling (OptiMASS) Research Group, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Melaka, Malaysia.

Abstract

In this paper, we present improved rice detection for rice grading quality. Indeed, the agricultural industry sector, especially in rice production has a long-established history so far in Malaysia. Quality evaluation of grains is a major challenge previously. The main objective is to make the differentiation and classification of head and broken rice grains utilizing image processing technique. The classification of rice grain is implemented based on the size of the grain (head rice or broken). Moore-Neighbor Tracing method is used in order to locate or detect the rice around the image. Based on the result from analysis proved that perimeter is the main feature to be considered for rice grading since its give significant correlation compared to other properties. In conclusion, by using Moore-Neighbor Tracing techniques, we can identify the right quantity of rice grain up to 95.83 %.

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Published

2016-05-01

How to Cite

Piramli, M., Rahman, A., & Abdullah, S. (2016). Rice Grain Grading Classification Based On Perimeter Using Moore-Neighbor Tracing Method. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(2), 23–27. Retrieved from https://jtec.utem.edu.my/jtec/article/view/940

Issue

Vol. 8 No. 2: Pioneering Future Innovation Through Green Technology I

Section

Articles

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