Image analysis methods for real-time color grading of stonefruit

Singh, Nalin; Delwiche, M. J.; Johnson, RB

doi:10.1016/0168-1699(93)90030-5

Cited by 32 publications

(8 citation statements)

References 8 publications

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“…In this case, the shape, color and size should be analyzed simultaneously to evaluate the quality appropriately. Some studies evaluated three or more characteristics such as the color, shape and size of fruit (Singh et al, 1993), e.g., a tomato grading system (Sarkar et al, 1984;Jahns et al, 2001;Clement et al, 2012) and an automated strawberry grading system (Liming and Yanchao, 2010). However, they only evaluated simple features such as the dominant color of the fruit surface, fruit diameter ratios and the minimum curvature of the boundary, which are not sufficient to describe the complex appearance of agricultural products.…”

Section: Introductionmentioning

confidence: 99%

Strawberry cultivar identification and quality evaluation on the basis of multiple fruit appearance features

Yamamoto

Ninomiya

Kimura

et al. 2015

Computers and Electronics in Agriculture

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The appearances of agricultural  products are important indices for evaluating the quality of commodities and the characteristics of different varieties. In general, the appearances are evaluated by experts based on visual observations. However, the concern regarding this method is that it lacks objectivity, and it is not quantifiable because it depends greatly on an empirical knowledge. In addition, agricultural products have multiple appearance features; therefore, several of them need to be analyzed simultaneously for correct evaluation of the appearance. In this study, we developed a new image analysis system that can simultaneously evaluate multiple appearance characteristics such as the color, shape and size, of agricultural products in detail. To evaluate the effectiveness of this system, we conducted quality evaluations and cultivar identification on the basis of cluster analysis, multidimensional scaling and discriminant analysis of the appearance characteristics. The results of the cluster analysis revealed that strawberries could be classified on the basis of their appearance characteristics. Furthermore, we were able to visualize the small differences in the appearance of the fruit based on multiple characteristics on a two-dimensional surface by performing multidimensional scaling. The results demonstrate that our system is effective for qualitative evaluations of the appearance of strawberries. The results of the discriminant analysis revealed that the accuracy of strawberry cultivar classification using 14 cultivars was <42%, when only single feature was used. However, the rate increased to 68% after combining the three features. These results indicate that our system exploits the advantage of analyzing multiple appearance characteristics.

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Section: Introductionmentioning

confidence: 99%

Strawberry cultivar identification and quality evaluation on the basis of multiple fruit appearance features

Yamamoto

Ninomiya

Kimura

et al. 2015

Computers and Electronics in Agriculture

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show abstract

“…Image processing offers solution for sorting of fruits based on their shape. Colour is also an important quality factor that has been widely studied [11][12][13][14]. The colour of an object is determined by wavelength of light reflected from its surface.…”

Section: Size Shape and Color Analysismentioning

confidence: 99%

Application of Computer Vision Technique on Sorting and Grading of Fruits and Vegetables

2015

J Food Process Technol

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“…For color evaluation of edible beans, Chtioui et al (2003) evaluated both RGB as well as HLS coordinates. RGB color coordinates were used for locating citrus fruits for harvesting (Jimenez et al 2000) and RGB color space was utilized along with Bayes' decision theory for image partitioning and subsequent color classification of stoned fruits (Singh et al 1993). To identify and quantify fat in meat images, RGB color space was used with a rectangular prism and Mahalano bois distance criteria (Gerrard et al 1996).…”

Section: Image Analysis and Understandingmentioning

confidence: 99%

Nondestructive Evaluation of Food Quality

Jha¹

2010

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Image analysis methods for real-time color grading of stonefruit

Cited by 32 publications

References 8 publications

Strawberry cultivar identification and quality evaluation on the basis of multiple fruit appearance features

Strawberry cultivar identification and quality evaluation on the basis of multiple fruit appearance features

Application of Computer Vision Technique on Sorting and Grading of Fruits and Vegetables

Nondestructive Evaluation of Food Quality

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