Oil palm fruit bunch grading system using red, green and blue digital number

被引：50
作者：
Alfatni, Meftah Salem M. [1 ]
Shariff, Abdul Rashid Mohamed [1 ]
Shafri, Helmi Zulhaidi Mohd [1 ]
Saaed, Osama M. Ben [1 ]
Eshanta, Omar M. [2 ]
机构：
[1] Faculty of Engineering, University Putra Malaysia, 43400 Serdang, Selangor
[2] Faculty of Engineering, University Kebangsaan Malaysia, 43600 Bangi, Selangor
来源：
Journal of Applied Sciences | 2008年 / 8卷 / 08期
关键词：
Color; Digital number; Fruit bunch; Grading system; Oil palm; Ripeness;
D O I：
10.3923/jas.2008.1444.1452
中图分类号：
学科分类号：
摘要：
This research deals with the ripeness grading of oil palm fruit bunches. The current practice in the oil palm mills is to grade the oil palm bunches manually using human graders. This method is subjective and subject to disputes. In this research, we developed an automated grading system for oil palm bunches using the RGB color model. This grading system was developed to distinguish between the three different categories of on palm truit bunches. The maturity or color ripening index was based on different color intensity. Our grading system employs a computer and camera to analyze and interpret images equivalent to the human eye and brain. The colors namely Red, Green and Blue (RGB) of the palm oil fruit bunch were investigated using this grading system. The computer program developed and used the mean color intensity to differentiate between the different color and ripeness of the fruits such as oil palm FFB. The program results showed that the ripeness of fruit bunch could be differentiated between different categories of fruit bunches based on RGB intensity. © 2008 Asian Network for Scientific Information.
引用
收藏
页码：1444 / 1452
页数：8
相关论文
共 10 条
  • [1] Aleksander S., Igor K., Information stored in coronas of fruits and leaves, (2002)
  • [2] Devrim U., Bernard G., Stem-end/calyx detection in apple fruits comparison of feature selection methods and classes. TCTS Lab, Faculté Polytechnique de Mons, Multitel Building, Avenue Copernic 1, Parc Initialis, (2004)
  • [3] Edreschi F.P., Mery D., Endoza F.M., Aguilera J.M., Classification of potato chips using pattern recognition, J. Food Sci, 69, (2004)
  • [4] Lopez Camelo A.F., Gomez P.A., Comparison of color indexes for tomato ripening, Hortic. Brasil. Brasíl, 22, pp. 534-537, (2004)
  • [5] Raji A.O., Alamutu A.O., Prospects of computer vision automated sorting systems in agricultural process operations in Nigeria. Agricultural Engineering International. CIGR, J. Sci. Res. Dev, 7, pp. 1-12, (2005)
  • [6] Rao S.P., Gopal A., Revathy R., Meenakshi K., Colour analysis of fruits using machine vision system for automatic sorting and grading, J. Instrum. Soc. India, 34, pp. 284-291, (1999)
  • [7] Rao S.P., Gopal A., Iqbal S., Revathy R.M., Meenakshi K., Classification of fruits based on shape using image processing techniques, J. Instrum. Soc. India, 34, pp. 277-239, (1999)
  • [8] Rashid S., Nor A.A., Radzali M., Shattri M., Rohaya H., Roop G., Correlation between oil content and DN, (2002)
  • [9] Saad A.A., Rashid S., Halim S., Thomas C., Fakhrul-Razi A., Optimizing the correlation between percentages of the oil content in palm oil fruit lets and digital number of images system, Faculty of Engineering, (2003)
  • [10] Wan Ishak W., Mohd Z.B., Abdul Malik A.H., Optical properties for mechanical harvesting of oil palm Ffb, J. Oil Palm Res, 12, pp. 38-45, (2000)
1