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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Indah Mustika Sakti
Universitas Brawijaya
Computer Science & IT

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Image Analysis using Color Co-occurrence Matrix Textural Features for Predicting Nitrogen Content in Spinach Yusuf Hendrawan; Indah Mustika Sakti; Yusuf Wibisono; Muchnuria Rachmawati; Sandra Malin Sutan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.10326

Abstract

This study aimed to determine the nitrogen content of spinach leaves by using computer imaging technology. The application of Color Co-occurrence Matrix (CCM) texture analysis was used to recognize the pattern of nitrogen content in spinach leaves. The texture analysis consisted of 40 CCM textural features constructed from RGB and grey colors. From the 40 textural features, the best features-subset was selected by using features selection method. Features selection method can increase the accuracy of image analysis using ANN model to predict nitrogen content of spinach leaves. The combination of ANN with Ant Colony Optimization resulted in the most optimal modelling with mean square error validation value of 0.0000083 and the R2 testing-set data = 0.99 by using 10 CCM textural features as the input of ANN. The computer vision method using ANN model which has been developed can be used as non-invasive sensing device to predict nitrogen content of spinach and for guiding farmers in the accurate application of their nitrogen fertilization strategies using low cost computer imaging technology.
Co-Authors Muchnuria Rachmawati Sandra Sandra Yusuf Hendrawan Yusuf Wibisono