Golden Ratio-Based Assessment of Nam Dok Mai Mango Shape Using Image Processing

Abstract

This study presents an application of the golden ratio (<p - 1.618) to evaluate the shape aesthetics of the Nam Dok Mai mango variety. Mango shape plays a critical role in determining both market value and consumer preferences. However, the assessment of visually appealing mango shapes based on human perception is inherently subjective and susceptible to inconsistencies. To address this, the proposed model utilizes one-dimensional (ID) top-view images processed using automated image analysis techniques, including segmentation, contour detection, and feature extraction. Four geometric components ( G1, G2, G3, and G4 ) were derived from the images and statistically analyzed. The results revealed that the computed ratios closely aligned with the golden ratio. The experiment was conducted using a dataset of 100 Nam Dok Mai mangoes. The shapes perceived as visually desirable by the human evaluators corresponded closely with those identified by the model as exhibiting golden ratio proportions. Furthermore, for each mango, consistent values of G1 through G4 were obtained from both the top A and top B views, confirming the model's repeatability across symmetrical perspectives. This study demonstrates the potential of incorporating mathematical aesthetics, specifically the golden ratio, into agricultural quality assessment frameworks to enhance objectivity and standardization in fruit grading.