Image Processing Techniques for Harumanis Disease Severity and Weighting Estimation for Automatic Grading System Application

Authors

  • N.S. Khalid School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Arau, Perlis
  • A.H. Abdullah School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Arau, Perlis
  • S.A.A. Shukor School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Arau, Perlis
  • Fathinul Syahir A.S. School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Arau, Perlis
  • S.C. Chau School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Arau, Perlis
  • N.D.N. Dalila Malaysian Agricultural Research and Development Institute (MARDI) Sintok, 06050 Bukit Kayu Hitam, Kedah.
  • H. Mansor School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Kampus Pauh Putra, 02600 Arau, Perlis

Keywords:

Image Processing, Disease Severity, Harumanis, Weight Estimation,

Abstract

Harumanis Mango is known as the king of Mangoes. It is very nutritious and rich with carotenes. However, many of the farmers and agriculture experts reported that they have problems in grading and inspecting the Harumanis Mango. Sometimes, Mango production loses its quality due to diseases that are not even visible to the naked eyes. Traditionally, farmers and agriculture experts will estimate the severity of the disease using their experiences. While for weight estimation, manual inspection was done by using a weight scale. This traditional method has its own drawbacks as it can lead to some errors due to inconsistencies made by human inspection. Furthermore, they are less efficient and very time-consuming. Therefore, an automated procedure that able to classify the disease severities and weight estimations would be much appreciated. With the aid of image processing techniques, diseases can be classified according to its scale, and its weight can be estimated. A number of pixels of Harumanis Mango will be used for classification. The analysis will be done by using the statistical method of regression. It shows that the accuracy of weight estimation is 72.25%.

References

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Published

2018-05-30

How to Cite

Khalid, N., Abdullah, A., Shukor, S., A.S., F. S., Chau, S., Dalila, N., & Mansor, H. (2018). Image Processing Techniques for Harumanis Disease Severity and Weighting Estimation for Automatic Grading System Application. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-15), 89–93. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4052

Issue

Vol. 10 No. 1-15: Exploring Man-Machines Compliance in Robotics and Image Processing

Section

Articles

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