Image feature based detection of agricultural quarantine materials in X-ray images

Toyofuku, Natsuko; Schatzki, Thomas F.

doi:10.1016/j.jairtraman.2007.06.001

Cited by 5 publications

(5 citation statements)

References 16 publications

(19 reference statements)

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“…Recent advances in X-ray radiography methods are dedicated to improving image contrast (Nielsen et al 2013, Haff 2008, more accurate and fast image segmentation methods (Mathanker et al 2010), image texture analysis (Toyofuku & Schatzki 2007), and machine learning classification (Mathanker et al 2011). Although most applications rely on the absorption contrast between defects and the product, in transmission radiography, newer developments such as phase contrast and dark-field imaging using grating interferometry have been proposed (Nielsen et al 2013).…”

Section: X-ray Radiographymentioning

confidence: 99%

Nondestructive Measurement of Fruit and Vegetable Quality

Nicolaı̈

Defraeye

Ketelaere

et al. 2014

Annu. Rev. Food Sci. Technol.

164

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We review nondestructive techniques for measuring internal and external quality attributes of fruit and vegetables, such as color, size and shape, flavor, texture, and absence of defects. The different techniques are organized according to their physical measurement principle. We first describe each technique and then list some examples. As many of these techniques rely on mathematical models and particular data processing methods, we discuss these where needed. We pay particular attention to techniques that can be implemented online in grading lines.

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Section: X-ray Radiographymentioning

confidence: 99%

Nondestructive Measurement of Fruit and Vegetable Quality

Nicolaı̈

Defraeye

Ketelaere

et al. 2014

Annu. Rev. Food Sci. Technol.

164

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“…Efforts to protect agricultural crops from invasion by foreign pests make this area of study particularly crucial. Generally these problems are mitigated with extensive X-ray inspection experience which is expensive and time-consuming (Toyofuku and Schatzki, 2007). If the inspector finds anything in the image that looks suspicious, the luggage is diverted to a hand inspection station (Schatzki, 1991).…”

Section: Luggage Inspection For Contraband Food Productsmentioning

confidence: 99%

“…More recently, Toyofuku and Schatzki (2007) examined the types of image features, other than just round objects, that would most reliably signal the presence of agricultural products. They found that by expanding the feature set to include round, tubes and granular with subset modifiers of dense and moon cake (named because of the very distinct features of this product), they could produce very promising and consistent inspection results at real-time inspection rates.…”

Section: Luggage Inspection For Contraband Food Productsmentioning

confidence: 99%

Computer vision for foreign body detection and removal in the food industry

Toyofuku¹,

Haff²

2012

Computer Vision Technology in the Food and Beverage Industries

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“…It is meaningful to develop efficient methods for early detection and prompt action against AQMs. Many studies have been performed in an attempt to find the fastest, most accurate and cost-effective methods to detect AQMs, such as X-ray imaging, 1,2 nuclear magnetic resonance (NMR) 3,4 and odor detection. 5–8 Among these methods, sniffer dogs have been recognized as one of the most commonly used method.…”

Section: Introductionmentioning

confidence: 99%