Abstract
Fruit ripeness identification is hard to measure especially when it involves color as main indicator. Suitable color model must be chosen to determine the right color for the ripeness identification. Hue, Saturation and Value (HSV) are proved to be a better choice because it can define the color intensity. Besides, it also helps to choose colors which are similar to the eyes. Manual grading process by human graders at oil palm mills lead to misconduct and mistakenly claimed unripe fruits as the ripe ones. This will cause trouble when the error report arrives at the production site for the oil production sterilization process. Furthermore, research done by the Federal Land Development Authority (FELDA) in Malaysia stated that an approximation of 60% palm oil are coming from ripe fruit meanwhile 40% are from underripe and 20% from unripe fruit minus water and dirt. This is proved the importance of identifying the right fruits for the purpose of oil palm production is extremely important. This paper studies the use of elimination method and nearest neighbor for oil palm fruit ripeness indicator. Result shows value gives the best indicator by providing the highest recognition rate towards ripe and unripe category.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alfatni, M.S.M., Mohamed Sharif, A.R., Mohamad Shafri, H.Z.: Oil Palm Fruit Bunch Grading System Using Red, Green and Blue Digital Number. Journal of Applied Sciences 8(8), 1444–1452 (2008)
Stoksik, M., Nguyen, D.T., Czemkowaki, M.: A Neural Net Based Color Recognition System. University of Tasmania, Australia
Lalanne, T., Lempereur, C.: Color Recognition with a Camera, A Supervised Algorithm Recognition, Toulouse Cedex, France
Peter, S.: Fundamentals of Computer Graphics. A K Peters, Ltd., Standford (2005); is a leading independent scientific technical publisher based in Wellesley, Massachusetts
Effendi, Z., Ramli, R., Ghani, J.A.: A Back Propagation Neural Networks for Grading Jatropha curcas Fruits Maturity. American Journal of Applied Sciences 7(3), 390–394 (2010); ISSN 1546-9239 © 2010 Science Publications
Yeow, Y.K., Abbas, Z., Khalid, K.: Application of Microwave Moisture Sensor for Determination of Oil Palm Fruit Ripeness. Measurement Science Review 10(1) (2010)
Omar, I., Khalid, M.A., Harun, M.H., Wahid, M.B.: Colour Meter For Measuring Fruit Ripeness. MPOB Information Series (2003)
Balasundram, S.K., Mohd Hanif, A.H., Abd Rahim, A.: computerized digital imaging technique to estimate palm oil content and quality based on fruit color
Tan, Y.A., Low, K.W., Lee, C.K., Sang, K.: Imaging technique for quantification of oil palm fruit ripeness and oil content. Eur. J. Lipid Sci. Technol. 112, 838–843 (2010)
Jaffar, A., Jaafar, R., Jamil, N., Low, C.Y., Abdullah, B.: Photogrammetric Grading of Oil Palm Fresh Fruit Bunches. International Journal of Mechanical & Mechatronics Engineering IJMMEÂ 9(10)
MPOB, Fresh Fruit Bunch Grading Manual. Ministry of Primary Industries, Malaysia (1995)
Alfatni, M.S.M., Mohamed Shariff, A.R., Mohd Shafri, H.Z., Ben, O.M., Eshanta, O.M.: Oil Palm Fruit Bunch Grading System Using Red, Green and Blue Digital Number. Journal of Applied Sciences 8(8), 1444–1452 (2008); ISSN 1812-5654 @ 2008 Asian Network for Scientific Information
Histogram Equalization. Wikipedia The Free Encyclopedia (2010)
NetMBA. Internet Center for Management and Business Administration, Inc. The Histogram, http://www.netmba.com/statistics/histogram/ (accessed)
Felda Agricultural Services Sdn Bhd. Analisa Oil MPD Kilang-Kilang FPISB (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Susilawati, M.F., Abdul Manaf, A., Chuprat, S. (2011). The Use of Elimination Method and Nearest Neighbor for Oil Palm Fruit Ripeness Indicator. In: Mohamad Zain, J., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22170-5_58
Download citation
DOI: https://doi.org/10.1007/978-3-642-22170-5_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22169-9
Online ISBN: 978-3-642-22170-5
eBook Packages: Computer ScienceComputer Science (R0)