Journal Article10.1016/J.JFOODENG.2012.09.017
Assessment of chestnut (Castanea spp.) slice quality using color images
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TL;DR: In this article, a computer vision methodology is proposed to sort chestnuts into five classes, as established by an expert human rater 1790 color images from slices with different quality classes were acquired, using a flat panel scanner, from the hybrid cultivar ‘Colossal’ and ‘Chinese seedlings.
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About: This article is published in Journal of Food Engineering. The article was published on 01 Apr 2013. The article focuses on the topics: Color image.
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Citations
Fruit classification using computer vision and feedforward neural network
TL;DR: A hybrid classification method based on fitness-scaled chaotic artificial bee colony (FSCABC) algorithm and feedforward neural network (FNN) was seen to be effective in classifying fruits.
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Detecting maturity of persimmon fruit based on image processing technique
TL;DR: In this paper, an automatic algorithm was developed to classify the persimmon fruits based on the external color of them, and two classifiers based on linear (LDA) and quadratic discriminant analysis (QDA) were used to assess the applicability of vision system.
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Assessment of internal quality of blueberries using hyperspectral transmittance and reflectance images with whole spectra or selected wavelengths
TL;DR: In this paper, a hyperspectral imaging system was used to acquire reflectance and transmittance images from 420 blueberries in three fruit orientations (i.e., stem end, calyx end and equator) for the spectral region of 400-1000nm.
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Qualitative analysis of edible oil oxidation using an olfactory machine
TL;DR: In this paper, an electronic nose was used to detect adulterations in edible oils, and the results were analyzed using cluster analysis, principal component analysis, support vector machine, quadratic discriminant analysis, and partial least squares regression technique.
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Automatic detection of orientation and diseases in blueberries using image analysis to improve their postharvest storage quality
TL;DR: This work proposes a pattern recognition method to automatically distinguish stem and calyx ends and detect damaged berries and results are promising because they will allow for the increase in export quality when implemented in production lines.
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References
Brief review of invariant texture analysis methods
Jianguo Zhang,Tieniu Tan +1 more
TL;DR: This paper considers invariant texture analysis, and approaches whose performances are not affected by translation, rotation, affine, and perspective transform are addressed.
Melting characteristics of cheese: analysis of effect of cheese dimensions using computer vision techniques
Hai-Hong Wang,Da-Wen Sun +1 more
TL;DR: In this paper, the influence of the area/thickness of slices on the melting property of Cheddar and Mozzarella cheeses was investigated with a computer vision method using image analysis techniques.
Rotation-inv ariant texture classifica tion using feature distrib utions
Matti Pietikäinen,Timo Ojala,Zelin Xu +2 more
TL;DR: A distribution-based classification approach and a set of recently developed texture measures are applied to rotation-invariant texture classification and the results show much better performance for this approach than for the CSAR features.
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Computer Vision
George Stockman,Linda G. Shapiro +1 more
- 02 Feb 2001
TL;DR: Computer Vision presents the necessary theory and techniques for students and practitioners who will work in fields where significant information must be extracted automatically from images, a useful resource book for professionals and a core text for both undergraduate and beginning graduate computer vision and imaging courses.
Development of a computer vision system to measure the color of potato chips
TL;DR: The implemented computer vision system can be used to study as well foods different from potato chips by selecting their proper settings for image acquisition and digital image processing.