Taste characterization of orange using image processing combined with ANFIS

被引：16

作者：

Adelkhani, Ali ^{[1
]}

Beheshti, Babak ^{[2
]}

Minaei, Saeid ^{[3
]}

Javadikia, Payam ^{[4
]}

Ghasemi-Varnamkhasti, Mahdi ^{[5
]}

机构：

[1] Islamic Azad Univ, Kermanshah Branch, Dept Agr Machinery Engn, Kermanshah, Iran

[2] Islamic Azad Univ, Sci & Res Branch, Dept Agr Machinery Engn, Tehran, Iran

[3] Tarbiat Modares Univ, Dept Agr Machinery Engn, Tehran, Iran

[4] Razi Univ Kermanshah, Dept Agr Machinery Engn, Kermanshah, Iran

[5] Shahrekord Univ, Dept Mech Engn Agr Machinery, Shahrekord, Iran

来源：

MEASUREMENT | 2013年 / 46卷 / 09期

关键词：

Orange taste; Image processing; Machine vision; Artificial intelligence; Fuzzy logic; NEURO-FUZZY;

D O I：

10.1016/j.measurement.2013.06.052

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Alternative methods for taste evaluation of fruits are of great interest to the food industry. This paper deals with the application of ANFIS-based image processing to characterize orange taste. For this purpose, images of 300 orange samples (Bam, Khooni and Thompson varieties) were acquired using a camera and the relevant features were extracted. The features were RGB component, HSV component, texture features, major and minor diameters, area, circumference, R/G and R/B color component ratio and diameter ratio. A sensory test performed by ten panelists was used to provide the reference data for image analysis. Then, the features were entered as input to ANFIS, and taste class of the fruit was the output of ANFIS. Based on the results, the success rate for the taste classification of Bam, Khooni and Thompson orange varieties were found to be 96.6%, 93.3% and 93.3%, respectively. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：3573 / 3580

页数：8

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