Estimation of quality and maturity of mangoes using image analysis

Ankush Kumar. 2020. Estimation of quality and maturity of mangoes using image analysis. Dijon : Université de Bourgogne, 29 p. Thesis MSc : Computer Vision : Université de Bourgogne

Encadrement : Sarron, Julien ; Faye, Emile

Résumé : Quality and maturity estimation of mangoes are important for the organization of harvesting date and post-harvest conservation. Although extensive fruit quality estimations exist, they are mostly destructive in nature and available tools for non-destructive measurement based on quality assessment. Thus, non-destructive tools for an accurate estimation of the quality and the maturity of the fruit have yet to be developed, especially for smallholders. The aim of this study was to develop a tool for non-destructive assessment of quality and maturity of mangoes based on image analysis. This experiment studied 1040 lateral RGB images of 520 mangoes of different stages of maturity and harvested in two orchards in West Africa. Upon performing digital image segmentation on the images of mangoes, six image feature were calculated with the use of digital image processing functions in MATLAB and four destructive features were taken in consideration. Then, correlations between destructive and non-destructive features of mangoes were explored.

Mots-clés libres : Mango, Image analysis, Segmentation, Maturity

Auteurs et affiliations

• Ankush Kumar, Université de Bourgogne (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/599321/)

Métriques

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