Local Adaptive Thresholding of Pecan X-Ray Images: Reverse Water Flow Method

Mathanker, Sunil K.; Weckler, Paul; Wang, N.; Bowser, Timothy J.; Maness, Niels O.

doi:10.13031/2013.30054

Cited by 17 publications

(12 citation statements)

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“…20 Together with these ideal optoelectronic properties, the high atomic weight of the constituent elements render PVKs promising candidates for ionising radiation detector materials. PVKs were demonstrated as a direct detector material following the synthesis of millimeter-sized single crystals, with X-ray induced currents reported in CsPbBr 3 21 and MAPbI 3 22 crystals, and improvements in crystal quality 23 and device integration 24 advanced the field quickly. Direct Detectors have achieved ultralow detection limits (<10 nGys -1 ) 25,26 and up to 100 times the sensitivity of the a-Se counterpart 27 , for soft X-rays, making them exciting commercial prospects.…”

Section: Introductionmentioning

confidence: 99%

“…These energetic photons, typically kiloelectron volts and above, exhibit long penetration depths that exceed the millimetre scale 1 ( Fig. 1a ) and enable a diverse range of applications, including healthcare, 2 industrial screening, 3,4 non-destructive imaging, 5 spectroscopy, 6 astronomy, 7,8 and security. 9 The usefulness of ionising radiation is dependent on the radiation source, the sample, the associated interface electronics, dedicated image processing algorithms and, crucially, the radiation detector itself.…”

Section: Introductionmentioning

confidence: 99%

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Halide perovskites scintillators: unique promise and current limitations

et al. 2021

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Halide perovskites scintillators: unique promise and current limitations

et al. 2021

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show abstract

“…However, knowledge of the shape of the product is not necessary if the foreign object has significantly different X-ray absorption properties. Several algorithms can be applied to enhance foreign object detection by utilizing conventional filtering [ 11 ], local contrast enhancement [ 1 ], and local adaptive thresholding [ 12 ]. These methods do not require DEXA data and can be applied to a single projection.…”

Section: Related Workmentioning

confidence: 99%

Unsupervised Foreign Object Detection Based on Dual-Energy Absorptiometry in the Food Industry

et al. 2021

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X-ray imaging is a widely used technique for non-destructive inspection of agricultural food products. One application of X-ray imaging is the autonomous, in-line detection of foreign objects in food samples. Examples of such inclusions are bone fragments in meat products, plastic and metal debris in fish, and fruit infestations. This article presents a processing methodology for unsupervised foreign object detection based on dual-energy X-ray absorptiometry (DEXA). A novel thickness correction model is introduced as a pre-processing technique for DEXA data. The aim of the model is to homogenize regions in the image that belong to the food product and to enhance contrast where the foreign object is present. In this way, the segmentation of the foreign object is more robust to noise and lack of contrast. The proposed methodology was applied to a dataset of 488 samples of meat products acquired from a conveyor belt. Approximately 60% of the samples contain foreign objects of different types and sizes, while the rest of the samples are void of foreign objects. The results show that samples without foreign objects are correctly identified in 97% of cases and that the overall accuracy of foreign object detection reaches 95%.

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“…However, knowledge of the shape of the product is not necessary if the foreign object has significantly different Xray absorption properties. Several algorithms can be applied to enhance foreign object detection by utilizing conventional filtering [11], local contrast enhancement [1] and local adaptive thresholding [12]. This approach relies on the assumption that an absorption gradient on the border of the defect can be distinguished from gradients in the main object.…”

Section: Related Workmentioning

confidence: 99%

Unsupervised foreign object detection based on dual-energy absorptiometry in the food industry

Andriiashen¹,

Liere²,

Leeuwen³

et al. 2021

Preprint

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X-ray imaging is a widely used technique for nondestructive inspection of agricultural food products. One application of X-ray imaging is the autonomous, in-line detection of foreign objects in food samples. Examples of such inclusions are bone fragments in meat products, plastic and metal debris in fish, fruit infestations.This article presents a processing methodology for unsupervised foreign object detection based on dual-energy X-ray absorptiometry (DEXA). A foreign object is defined as a fragment of material with different X-ray attenuation properties than those belonging to the food product. A novel thickness correction model is introduced as a pre-processing technique for DEXA data. The aim of the model is to homogenize regions in the image that belong to the food product and enhance contrast where the foreign object is present. In this way, the segmentation of the foreign object is more robust to noise and lack of contrast.The proposed methodology was applied to a dataset of 488 samples of meat products. The samples were acquired from a conveyor belt in a food processing factory. Approximately 60% of the samples contain foreign objects of different types and sizes, while the rest of the samples are void of foreign objects. The results show that samples without foreign objects are correctly identified in 97% of cases, the overall accuracy of foreign object detection reaches 95%.

show abstract

Local Adaptive Thresholding of Pecan X-Ray Images: Reverse Water Flow Method

Cited by 17 publications

References 0 publications

Halide perovskites scintillators: unique promise and current limitations

Halide perovskites scintillators: unique promise and current limitations

Unsupervised Foreign Object Detection Based on Dual-Energy Absorptiometry in the Food Industry

Unsupervised foreign object detection based on dual-energy absorptiometry in the food industry

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