Development of a machine vision system for automatic date grading using digital reflective near-infrared imaging

Lee, Dah-Jye; Schoenberger, Robert B.; Archibald, James K.; McCollum, Steve

doi:10.1016/j.jfoodeng.2007.10.021

Cited by 92 publications

(38 citation statements)

References 27 publications

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“…Al-Janobi (2000) graded Saudi dates (Sifri variety) based on colour and texture with an average error of 1.8% using a colour camera. A computer vision system for the grading of dates based on fruit size and skin delamination using reflected NIR imaging showed 10% higher accuracy over human inspection and a reduction in labor cost by 75% (Lee et al, 2008b). In another study, using a RGB colour imaging system to grade dates into 3 categories based on size, shape, flabbiness intensity and defects yielded 80% accuracy (Al-Ohali, 2011).…”

Section: Introductionmentioning

confidence: 99%

Computer vision technique to classify dates based on hardness

Manickavasagan

Al-Shekaili

Al-Mezeini

et al. 2018

Jour. Agri. & Mar. Scie.

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Hardness is one of the important attributes in determining the quality of dried fruits. Hardness assessment is normally carried out by manual inspection. This method is time consuming, laborious, expensive and subjective. The objective of this study was to develop a computer vision system with a monochrome camera to classify dates based on hardness. Date samples were obtained from three different growing regions in Oman and graded into soft, semi-hard, and hard classes based on hardness. A total of 1800 date samples were imaged individually using a monochrome camera (600 dates / class). Histogram and texture features were extracted from the acquired monochrome images and used in the classification models. The overall classification accuracies in three class model (soft, semi-hard, and hard) were 66% and 71% for linear discriminant analysis (LDA) and artificial neural network (ANN), respectively. It was improved to 84% and 77% in LDA and ANN, respectively while using two class model (soft and hard (semi-hard and hard together)). The histogram features were more contributing in the date classification based on hardness than image texture features. Computer vision technique has great potential to develop online quality monitoring systems for dates and other dried fruits.

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Section: Introductionmentioning

confidence: 99%

Computer vision technique to classify dates based on hardness

Manickavasagan

Al-Shekaili

Al-Mezeini

et al. 2018

Jour. Agri. & Mar. Scie.

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“…Xue et al [11] tested the external natural damage and internal soluble solids content of Huping Jujube through models by using hyperspectral imaging technology. Lee et al [12,13] took with the size and maturity of Yezao as the grading indexes, in which the maturity index was determined by the surface color, and proposed a color space conversion and color distribution analysis technology. Linear calibration system of surface color and maturity was established and the robustness is relatively high.…”

Section: Introductionmentioning

confidence: 99%

Analysis of moisture and total sugar content of Huizao based on surface images

Zhang

et al. 2018

International Journal of Agricultural and Biological Engineering

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Moisture and total sugar content are two important internal qualities of Huizao. In order to explore their correlation with external qualities, a novel method of moisture and total sugar content analysis was proposed based on surface images. Firstly, five geometric features and seven texture features of Huizao were obtained to be the external quality indexes by digital image processing technology. Secondly, the wrinkle degree as an important index was extracted by marked watershed segmentation algorithm. According to the external quality the Huizao samples were grouped, and the moisture and total sugar content were determined through physical and chemical methods. Lastly, the moisture and total sugar content and twelve external indexes were all processed by step discriminatory analysis. Meanwhile, the regression models of moisture content with short diameter, contrast, and wrinkle degree and total sugar with wrinkle degree were established. The coefficients of the model were 0.9992 and 0.9978 respectively, and all the significance was less than 0.01, which show that the regression equation and regression coefficient effect are highly significant. The results indicate that the moisture and total sugar content of Huizao are greatly correlated with the wrinkle degree. The moisture and total sugar content are the highest when the wrinkle degree is at 2 to 3 grade, and they decrease gradually with the wrinkle degree increasing. Moisture content shows positive correlation with the size of Huizao. The results of model analysis agree well with the experimental results, which can provide valuable reference for improving Huizao grade diversity.

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“…The image acquisition and processing technique have created new food quality monitoring methods. It has good accuracy to appearance geometric measurement [9][10][11]. Hassan et al used a white paper between impression inky sample and disk plunger, and then the footprint of sample contact area was scanned and processed to determine the contact surface area [7].…”

Section: Introductionmentioning

confidence: 99%

Stress relaxation of date at different temperature and moisture content of product: A new approach

Zare¹,

Alirezaei²,

Nassiri³

2012

2012 Dallas, Texas, July 29 - August 1, 2012

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Abstract-Iran is one of the greatest producers of date in the world. However due to lack of information about its viscoelastic properties, much of the production downgraded during harvesting and postharvesting processes. In this study the effect of temperature and moisture content of product were investigated on stress relaxation characteristics. Therefore, the freshly harvested date (kabkab) at tamar stage were put in controlled environment chamber to obtain different temperature levels (25, 35, 45, and 55 0 C) and moisture contents (8.5, 8.7, 9.2, 15.3, 20, 32.2 %d.b.). A texture analyzer TAXT2 (Stable Microsystems, UK) was used to apply uniaxial compression tests. A chamber capable to control temperature was designed and fabricated around the plunger of texture analyzer to control the temperature during the experiment. As a new approach a CCD camera (A4tech, 30 fps) was mounted on a cylindrical glass probe to scan and record contact area between date and disk. Afterwards, pictures were analyzed using image processing toolbox of Matlab software. Individual date fruit was uniaxially compressed at speed of 1 mm/s. The constant strain of 30% of thickness of date was applied to the horizontally oriented fruit. To select a suitable model for describing stress relaxation of date, experimental data were fitted with three famous stress relaxation models including the generalized Maxwell, Nussinovitch, and Pelege. The constant in mentioned model were determined and correlated with temperature and moisture content of product using non-linear regression analysis. It was found that Generalized Maxwell and Nussinovitch models appropriately describe viscoelastic characteristics of date fruits as compared to Peleg mode.

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Development of a machine vision system for automatic date grading using digital reflective near-infrared imaging

Cited by 92 publications

References 27 publications

Computer vision technique to classify dates based on hardness

Computer vision technique to classify dates based on hardness

Analysis of moisture and total sugar content of Huizao based on surface images

Stress relaxation of date at different temperature and moisture content of product: A new approach

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