Nondestructive maturity classification of durian based on fractal features

This paper proposes a classification method to determine maturity levels of durian by using fractal analysis. We used the automatic knocking machine to knock the durian in which the knocked-sound was analyzed in terms of fractal concepts, and the fractal dimension (FD) values to be presented as a feature. The fractal algorithm, namely, Higuchi´s method was selected to evaluate FD of the knocked-sound. To show the FD changes in waveform with respect to the time, the time-dependent FD (TDFD) was proposed. Probability distribution of TDFDs indicates that the relationship of immaturity and maturity levels of durian has proven that the FD-based features can be employed. The proposed method achieves an average accuracy rate of 89.94% and 88.20% for the Montong durians weighing 3.5-4.0 kg and 4.0-4.5 kg, respectively. The experimental results show that the FD is capable of classifying maturity levels of durian effectively.