Study and classification of the Crystallographic Orientation Distribution Function of a non-grain oriented electrical steel using computer vision system

Abstract The aims of this study were to obtain percentages of meat and fat cover for SEUROP classification system reference images using a computer vision system (CVS) and to calculate classification intervals which could be used in the future for construction of cheap and easy to use classification devices for small slaughterhouses. Lowest percentages of fat cover were found for the first class marked as “low” (the lowest fat content) and they gradually increased to the last class marked as “very high” (the highest fat content). Based on the obtained results, decision making intervals were proposed. In the present study, classification only refers to classification of adult bovine animals based on fat cover.

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Computer vision system and near-infrared spectroscopy for identification and classification of chicken with wooden breast, and physicochemical and technological characterization

Infrared Physics & Technology ◽

10.1016/j.infrared.2018.11.036 ◽

2019 ◽

Vol 96 ◽

pp. 303-310 ◽

Cited By ~ 11

Author(s):

Bruna Caroline Geronimo ◽

Saulo Martiello Mastelini ◽

Rafael Humberto Carvalho ◽

Sylvio Barbon Júnior ◽

Douglas Fernandes Barbin ◽

...

Keyword(s):

Computer Vision ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Vision System ◽

Computer Vision System ◽

Wooden Breast

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Study on Color Classification of Pork with Computer Vision System Based on Different Color Difference Formula

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.474-476.1638 ◽

2011 ◽

Vol 474-476 ◽

pp. 1638-1642 ◽

Cited By ~ 1

Author(s):

Hong Xia Zhao ◽

Zhi Yang Luo ◽

Xin Yuan ◽

Yuan Li

Keyword(s):

Computer Vision ◽

Color Change ◽

Vision System ◽

Close Relation ◽

Color Difference ◽

Computer Vision System ◽

Color Classification ◽

Difference Formula ◽

Different Color

The bad degree of meat and the color change have a close relation. Computer vision is not under the influence of physiological and psychological factor of person; Appraisement standard is objective and steady. Therefore, computer vision system has been established, which can do collection, management, display, and appraisement of porky color. The CIEL*a*b* and CIEDE2000 color difference formula were introduced into the classification of pork, the result was identical. Because the calculation course of CIEDE2000 color difference is complex, so the CIE1976L*a*b* color difference is still adopted to calculate color change at actual production.

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A crystallographic approach to the calculation of orientation diagrams

Canadian Journal of Earth Sciences ◽

10.1139/e83-083 ◽

1983 ◽

Vol 20 (6) ◽

pp. 932-952 ◽

Cited By ~ 2

Author(s):

John Starkey

Keyword(s):

Distribution Function ◽

Orientation Distribution Function ◽

Crystallographic Orientation ◽

Crystal Orientation ◽

Orientation Distribution ◽

Polycrystalline Aggregate ◽

Crystal Forms ◽

Pole Figures ◽

Orientation Matrix ◽

Multiplicity Factor

Methods are described that use measured pole figures directly to calculate pole figures, inverse pole figures, and the crystal orientation matrix; this latter is a frequency distribution of the Euler rotations, which relate the crystal orientations in a polycrystalline aggregate to a standard crystallographic orientation. It is demonstrated that if data from crystal forms with different crystallographic multiplicities are to be compared the appropriate multiplicity factor must be applied to the data in the measured pole figures.These techniques are applied to computer-simulated fabrics and the data obtained are compared with data derived via the orientation distribution function. It is concluded that the data derived directly from the measured pole figures more closely represent the actual data. In the case of inverse pole figures the procedures based on the orientation distribution function yield results that are of doubtful geological significance.

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