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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Computers and Electr...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Computers and Electronics in Agriculture
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2025
Data sources: DBLP
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Cracked egg recognition based on machine vision

Authors: Guanjun Bao; Mimi Jia; Yi Xun; Shibo Cai; Qinghua Yang;

Cracked egg recognition based on machine vision

Abstract

Abstract Since the cracks on eggshell are difficult to be recognized due to the surrounding highlighted dark spots on the egg surface under back-light illumination, a new method to identify the cracks based on machine vision was proposed. After analyzing the characteristics of the cracks in the image of the egg under the back-light illumination, a negative LOG (Laplacian of Gaussian) operator was employed to effectively enhance the cracks in the egg image. Then the Hysteresis thresholding algorithm was adopted to acquire the proper thresholds, which eliminated the irrelevant dark spots in the binary egg image and ensured the continuity of the cracks. Finally, the improved LFI (Local Fitting Image) index was used to distinguish the crack region from the mislabeled region. The experimental results showed that the proposed method was effective in cases of complicated egg surface conditions, such as irregular dark spots and invisible micro-cracks, with cracked egg recognition rate of 92.5%.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
55
Top 1%
Top 10%
Top 10%
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