Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i29/58582
Year: 2016, Volume: 9, Issue: 29, Pages: 1-5
Original Article
Suhartono*
State Islamic University of Maulana Malik Ibrahim Malang, [email protected]
*Author for correspondence
Suhartono
State Islamic University of Maulana Malik Ibrahim Malang,
Email: [email protected]
Background/Objectives: To improve an identification of chlorophyll content in leaf, this paper presents an implementation of a supervised learning method based on membership function training in the context of mamdani fuzzy models. Methods/ Statistical Analysis: this paper presents a fuzzy rule based algorithm; natural color image in leaf (Red, Green and Blue) is used as the input to the fuzzy mamdani models. The output of the fuzzy mamdani models is value of chlorophyll content. Results: The proposed approach was superior to identification of chlorophyll content in leaf using image processing technique and mamdani fuzzy method has higher identification accuracy. Conclusion/Application: Finally, the basic difference of value of chlorophyll content between fuzzy mamdani models and the actual was less than 3,1 % on average.
Keywords: Chlorophyll Content, Identification, Image Processing, Leaf, Mamdani Fuzzy
Subscribe now for latest articles and news.
