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ABSTRACT AN image processing algorithm was developed for detecting stress cracks in corn kernels using a commercial vision system. White light in back-lighting mode with black-coated background having a small aperture for the light provided the best viewing conditions. The kernel images, when processed using the algorithm developed, produced white streaks
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ABSTRACT AN image processing algorithm was developed for detecting stress cracks in corn kernels using a commercial vision system. White light in back-lighting mode with black-coated background having a small aperture for the light provided the best viewing conditions. The kernel images, when processed using the algorithm developed, produced white streaks
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For automatic detection of corn stress cracks, a machine vision system was developed, which simulates the processes that the human visual system uses to perceive the stress cracks from the corn kernel in the conventional candling method. The automatic stress crack detection system consisted of four consecutive stages and was configured in ...
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An image processing algorithm was developed for detecting stress cracks in corn kernels using a commercial vision system. White light in back
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33% multiple stress cracked kernels, while that dried from near 20% moisture content had only 23% kernels of that category. Also, drying air temperatures of 60, 87, and 115°C resulted in 20, 30 and 34% stress-cracked kernels respectively. Yellow corn is more susceptible to multiple stress cracks than white (White and Ross,
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Detection of stress cracks in corn kernels using machine vision ... visual system uses to perceive the stress cracks from the corn kernel in the conventional candling method.The automatic stress crack detection system consisted of four consecutive stages and was configured in various ways by selecting different image processing algorithms in each stage.
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ABSTRACT AN image processing algorithm was developed for detecting stress cracks in corn kernels using a commercial vision system. White light in back-lighting mode with black-coated background having a small aperture for the light provided the best viewing conditions. The kernel images, when processed using the algorithm developed, produced white streaks
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A corn kernel classification procedure was developed in the frequency domain using a two-dimensional Fourier Transform for inspection of stress cracks. Investigations were also conducted to define suitable conditions and optimum image resolution for viewing stress cracks in corn kernels using a computer vision system. A pre-processing procedure included
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method is most suitable for automatic stress crack detection. Image processing was used to inspect stress cracks of corn kernels by Gunasekaran et al. (1987). The back lighting mode with a black-coated plate as a background was adopted to obtain images with high contrast between the stress cracks and the rest of the kernel. They developed image processing algorithms
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The detection of stress cracks remains one of the most important tasks in corn quality inspection. Such an index of quality would be helpful in assessing not only the end-use values of the corn but also the drying method used and the appropriateness of subsequent handling procedures.For automatic detection of corn stress cracks, a machine vision system was
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22/12/2018 Corn kernel, grading, image processing, support vector machine, ... The experimental results showed it was validated for breakage and visual inspection for cracks. Zapotoczny et al. 12 proposed a texture-based classification method for classifying 11 different quality grades of spring wheat and winter wheat varieties. Textures were computed separately
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Article. CHANGE OF STRESS CRACK IN CORN KERNEL DURING ITS PREPARATION FOR PROCESSING. July 2020; Grain Products and Mixed Fodder’s 20(2):14-18
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Abstract: Hot air drying is one of the most widely used techniques in large-scale processing of grain. However, the existing problem of grain hot air drying is the high cracking r
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28/05/2013 Stress cracks and other damage in corn kernels and soybeans have been detected successfully from their images. The shape features of food have been extracted using machine vision [ 4 ] and parameters such as area, length, width, and compactness of grain binary images [ 5 ] used to recognize wheat, oats, barley, and rye.
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Han et al. studied frequency domain image analysis for detecting stress cracks in corn kernels. A fast fourier transform algorithm was applied to the pre-processed images and the transformation results were condensed into seed feature signatures representing position or orientation invariant morphological features. Stress cracks are internal fissures that can be
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Wei Shuo,Chen Pengxiao,Xie Weijun,Wang Fenghe,Yang Deyong.Prediction of stress cracks in corn kernels drying based on three-dimensional heat and mass transfer[J].Transactions of t
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ABSTRACT AN image processing algorithm was developed for detecting stress cracks in corn kernels using a commercial vision system. White light in back-lighting mode with black-coated background having a small aperture for the light provided the best viewing conditions. The kernel images, when processed using the algorithm developed, produced white streaks
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22/12/2018 Corn kernel, grading, image processing, support vector machine, ... The experimental results showed it was validated for breakage and visual inspection for cracks. Zapotoczny et al. 12 proposed a texture-based classification method for classifying 11 different quality grades of spring wheat and winter wheat varieties. Textures were computed separately
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Download Citation Detection of surface cracks of corn kernel based on morphology The surface crack identification and detection of a corn kernel are
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Article. CHANGE OF STRESS CRACK IN CORN KERNEL DURING ITS PREPARATION FOR PROCESSING. July 2020; Grain Products and Mixed Fodder’s 20(2):14-18
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Abstract: Hot air drying is one of the most widely used techniques in large-scale processing of grain. However, the existing problem of grain hot air drying is the high cracking r
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Han et al. studied frequency domain image analysis for detecting stress cracks in corn kernels. A fast fourier transform algorithm was applied to the pre-processed images and the transformation results were condensed into seed feature signatures representing position or orientation invariant morphological features. Stress cracks are internal fissures that can be
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Title: CHANGE OF STRESS CRACK IN CORN KERNEL DURING ITS PREPARATION FOR PROCESSING: Authors: R. Rybchynskyi: Issue Date: 2020: Abstract:
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01/06/2020 The number of kernels per ear is one of the major agronomic yield indicators for maize. Manual assessment of kernel traits can be time consuming and laborious. Moreover, manually acquired data can be influenced by subjective bias of the observer. Existing methods for counting of kernel number are often unstable and costly. Machine vision technology allows
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28/06/2013 〔10〕Gunasekarans S，Cooper T M，et al. Image processing for stress crack in corn kernels[J]. Transactions of the ASAE，1987，30(1):266-271 〔11〕Zayas I， Lai F S， Pomeranz Y. Discrimination between wheat classes and varieties by im age analysis [J]. Cereal Chemistry，1986，63 (1):52-56 〔12〕Zayas I， Pormeranz Y， L ai F S. Discrimination of
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4 Gunasekaran S, Cooper T M, Berlage A G, et al. Image processing for stress cracks in corn kernels[J].Transactions of the ASAE,1987.30(1):266--271. 被引量：1; 5 Bowers S V, Dodd R B, Han Y J. Nondestructive testing to determine internal quality of fruit[J]. ASAE Paper.1988,88--6569. 被引量：1
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