COMPUTER APPLICATION ON PATTERN RECOGNITION FOR PALM-DATE GRADING | ||||
| Misr Journal of Agricultural Engineering | ||||
| Article 16, Volume 31, Issue 2, April 2014, Page 619-630 PDF (895.39 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjae.2014.99648 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| E.H Ewida1; M. N. El Awady2; M. A. Rashwan3; M. Z. ElAttar4 | ||||
| 1PhD student Agric. Eng. Dep. Faculty of agriculture, Ain shams univ., Egypt. | ||||
| 2Emir. Prof. Agric. Eng. Dep. Faculty of agriculture, Ain shams univ., Egypt. | ||||
| 3Prof. communication Dep. Faculty of engineering, Cairo univ., Egypt. | ||||
| 4Teacher Agric. Eng. Dep. Faculty of agriculture, Ain shams univ., Egypt. | ||||
| Abstract | ||||
| The current procedure in the palm date factories is grading the palm date fruit manually using human graders. This method is inconsistent because each grader has his own technique and may vary from one person to another. Hence, this affects the quality and quantity of the fruit that can be extracted. In this research, a new model for automated grading system of palm date fruit is developed using the RGB color, area, and texture of the fruit and artificial fuzzy logic is used as a classifier. The color model was based on different color intensities. The purpose of this sorting system is to distinguish between three different classes of palm date fruit which are (class A) the best grade among (class B) and (class C). The grading system uses a computer and an ordinary scanner to analyze and interpret images correspondent to human eye and mind. The computer program is developed using MATLAB language: image processing toolbox for the image processing part, and fuzzy logic toolbox for the classification part. The calculation is based on the fruit size, the mean color intensity based on RGB color model, and the texture. The decision making process used fuzzy logic to train the data and make the classification for the palm date fruit. A total of 570 date samples were used to build and train the system. The program developed has been able to distinguish the three different classes of palm date fruit automatically; with 99.8% of overall efficiency. This paper provides a very good technique to standardize the palm date fruit grading system over a large area. | ||||
| Keywords | ||||
| Pattern recognition; Image processing; Palm date fruit; Classification; Grading; and Fuzzy Logic | ||||
| References | ||||
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