Quantification of browning in apples using colour and textural features by image analysis

作     者：Srinivasagan N.Subhashree S.Sunoj Jun Xue Ganesh C.Bora 

作者机构：Agricultural and Biosystems EngineeringNorth Dakota State UniversityFargoNorth DakotaUSA Guelph Food Research CenterAgriculture and Agri-Food CanadaOntarioCanada Agricultural and Biological EngineeringMississippi State UniversityMississippiUSA 

出 版 物：《Food Quality and Safety》 (食品品质与安全研究（英文版）)

年 卷 期：2017年第1卷第3期

页      面：221-226页

核心收录：

学科分类：0832[工学-食品科学与工程（可授工学、农学学位）] 1004[医学-公共卫生与预防医学(可授医学、理学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：apple browning colour calibration image analysis textural features 

摘      要：This study analyses the effect of browning through image analysis based on colour and textural features in fresh-cut apple slices.A computer vision system(CVS)was developed for image acquisition,which consisted of a digital camera and a florescent lamp source for illumination with a contrasting background.The CVS was calibrated using standard colour values and a model was developed by artificial neural network technique.Three varieties of apples such as Honey crisp,Granny Smith,and Golden Delicious were used for the analysis.The apples were freshly cut and subjected to image acquisition.Normalized colour features(L*,browning index,hue,and colour change)and textural features(entropy,contrast,and homogeneity)were analysed from the acquired images.The varieties Honey Crisp and Granny Smith did undergo browning within 120 min,whereas Golden delicious did not brown significantly.The study concluded that colour and textural features were important decision features for detecting browning in apples through image analysis.