Recent developments in the applications of image processing techniques for food quality evaluation

Du, Cheng-Jin; Sun, Da‐Wen

doi:10.1016/j.tifs.2003.10.006

Cited by 484 publications

(216 citation statements)

References 121 publications

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“…They can also be applied to real food systems without alteration (Nott and Hall 1999). Increasing demands for objectivity, consistency and efficiency within the food industry, have necessitated the introduction of computer-based image processing techniques (Du and Sun 2004).…”

Section: Thermal Imaging (Ti) As a Process Analytical Technique In Thmentioning

confidence: 99%

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

et al. 2011

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Non-destructive systems are recent trends for quality evaluation of fruits and vegetables. Information on post-harvest variations in electrical properties is needed to develop new instruments for this purpose. Electrical properties are finding increasing application in agriculture and food processing industries. Knowledge of dielectric properties of foods as a function of moisture content and temperature is essential in the design and control of drying systems. As simple, rapid and non-destructive measuring techniques, dielectric spectroscopy provides information about the dielectric response of materials to electromagnetic field. Electrical properties of agricultural materials have been of interest for many years. The interest in dielectric properties of materials has historically been associated with the design of electrical equipment. This review paper covers theoretical aspects of different electrical properties, their measurement techniques, applications of dielectric properties in agriculture/food processing sector and potential applications of thermal imaging (TI) for quality and safety assessment in food processing. The values of dielectric properties of a number of products including food grains, fruits and vegetables, and meat and meat products are presented in table form. This comprehensive coverage will be useful for academic, scientific and industrial community in treating and applying the facts in developing/testing new processes and products based on electromagnetic energy application.Keywords Electrical properties . Non-destructive . Measuring techniques . Dielectric constant . Loss factor . Thermal imaging technique . Food quality evaluationThe material investigation and moisture measurement using electromagnetic waves in wide spectrum serve for quality control and improvement in many branches like industry, forest and wood-working industry, civil engineering, agriculture, commerce and also foods e.g. for quality evaluation of meat, fruits, coffee etc (Hlavacova 2003; Venkatesh and Raghavan 2004). Non-destructive evaluation of quality based on constituents of fruits and vegetables has been successfully used (Chen et al. 1999;Jha et al. 2001;Kawano 1998). Electrical characteristics of agricultural materials have been of interest for many years (Nelson 2006) and are utilized in many areas of human activities. Techniques for non-destructive determination of quality and related characteristics of agricultural products are helpful to producers, handlers and processors . Permittivity and moisture can be closely correlated when water content is high. Knowledge of dielectric properties in partially frozen material is critical in determining the rates and uniformity of heating in microwave thawing. Electrical properties are important in processing foods with pulsed electric fields, ohmic heating, induction heating, radio frequency, and microwave heating. These properties are also useful in the detection of processing conditions or the quality of foods (Barbosa-Canovas et al. 2006). Considering ...

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Section: Thermal Imaging (Ti) As a Process Analytical Technique In Thmentioning

confidence: 99%

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

et al. 2011

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“…Over the last two decades, image processing has been rapidly diffused in food industry as instrument for automatic food quality evaluation and control (Du and Sun, 2004;Jackman et al, 2012). Computer Vision Systems (CVSs) can effectively replace visual (human) inspection in different contexts of food industry.…”

Section: Introductionmentioning

confidence: 99%

“…Computer Vision Systems (CVSs) can effectively replace visual (human) inspection in different contexts of food industry. Furthermore, they provide more objective and standard evaluation of some food quality parameters over a great number of samples (Du and Sun, 2004; K. León et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Application of Computer Vision for quality control in frozen mixed berries production: colour calibration issues

Aimonino¹,

Gay²,

Comba³

2013

J Agricult Engineer

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Computer vision is becoming increasingly important in quality control of many food processes. The appearance properties of food products (colour, texture, shape and size) are, in fact, correlated with organoleptic characteristics and/or the presence of defects. Quality control based on image processing eliminates the subjectivity of human visual inspection, allowing rapid and non-destructive analysis. However, most food matrices show a wide variability in appearance features, therefore robust and customized image elaboration algorithms have to be implemented for each specific product. For this reason, quality control by visual inspection is still rather diffused in several food processes. The case study inspiring this paper concerns the production of frozen mixed berries. Once frozen, different kinds of berries are mixed together, in different amounts, according to a recipe. The correct quantity of each kind of fruit, within a certain tolerance, has to be ensured by producers. Quality control relies on bringing few samples for each production lot (samples of the same weight) and, manually, counting the amount of each species. This operation is tedious, subject to errors, and time consuming, while a computer vision system (CVS) could determine the amount of each kind of berries in a few seconds. This paper discusses the problem of colour calibration of the CVS used for frozen berries mixture evaluation. Images are acquired by a digital camera coupled with a dome lighting system, which gives a homogeneous illumination on the entire visible surface of the berries, and a flat bed scanner. RBG device dependent data are then mapped onto CIELab colorimetric colour space using different transformation operators. The obtained results show that the proposed calibration procedure leads to colour discrepancies comparable or even below the human eyes sensibility.

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“…There is a variety of image acquisition techniques available for the analysis of internal structures in food: ultrasound (amplitude modulation and brightness modulation), magnetic resonance imaging (MRI), computed tomography (based on X-ray attenuation), and electrical tomography (based on resistance, impedance, capacitance or electromagnetic inductance) (Du and Sun, 2004). Among these, MRI has the advantage of allowing a variety of measurements to be made that not only contribute to the evaluation of maturity and quality parameters in fruit and vegetables but also improve the understanding of underlying physiological processes (Butz et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…For the unsupervised mode the class label of the output regions are not provided a priori whereas for the supervised mode those values are. The segmentation techniques available may be grouped into four different categories: histogram-, region-, edge-and classification-based (Du and Sun, 2004).…”

Section: Introductionmentioning

confidence: 99%

Non-destructive seed detection in mandarins: Comparison of automatic threshold methods in FLASH and COMSPIRA MRIs

Elorza

Zheng

Sun

et al. 2008

Postharvest Biology and Technology

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Magnetic resonance imaging was used to acquire images of the internal structure of mandarins for non-destructive seed identification. Two different types of fast MRI sequences were investigated: a gradient echo and a spiral-radial, with 484 ms acquisition time for the former compared to 240 ms for the latter. The radial-spiral option allows over-sampling of the central area of the k-space maintaining the contrast within the MRI images and so the feasibility of seed segmentation. Three segmentation techniques were applied for image post-processing: region-based, onedimension histogram variance, and two-dimension histogram variance, among which the latter procedure has been demonstrated to give the most promising results. Image features including perimeter, compactness, maximum distance to the gravity centre, and aspect ratio were employed in a linear discriminant function, by which seed identification of mandarins could be achieved with 100% accuracy using radial-spiral sequence and 98.7% accuracy with gradient echo images.

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Recent developments in the applications of image processing techniques for food quality evaluation

Cited by 484 publications

References 121 publications

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review

Application of Computer Vision for quality control in frozen mixed berries production: colour calibration issues

Non-destructive seed detection in mandarins: Comparison of automatic threshold methods in FLASH and COMSPIRA MRIs

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