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פותח על ידי קלירמאש פתרונות בע"מ -
Detection of bruises in magnetic resonance images of apples
Year:
1995
Authors :
ציון, בועז
;
.
Volume :
13
Co-Authors:

Pictiaw Chen - Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA
Michael J. McCarthy - Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA

 

 

Facilitators :
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Total pages:
1
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Abstract:

A method for fast, computerized detection of bruises in magnetic resonance images (MRI) of apples was developed. It uses a simple thresholding technique combined with considerations of the apple geometry to distinguish between bright pixels representing the vascular system, and those representing bruises. The algorithm was tested on 20 images of ten Jonathan apples (before and after bruising), ten images of Golden Delicious apples and ten images of Hermon apples, and it demonstrated its ability to distinguish between bruised and non-bruised apples. This is the first step in the development of a sensing method using three-dimensional imaging and image analysis for detection of bruises.

Note:
Related Files :
Apple
bruising
GOLDEN DELICIOUS
Magnetic resonance imaging (MRI)
עוד תגיות
תוכן קשור
More details
DOI :
10.1016/0168-1699(95)00027-5
Article number:
0
Affiliations:
Database:
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
49930
Last updated date:
02/03/2022 17:27
Creation date:
13/09/2020 16:09
Scientific Publication
Detection of bruises in magnetic resonance images of apples
13

Pictiaw Chen - Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA
Michael J. McCarthy - Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA

 

 

Detection of bruises in magnetic resonance images of apples

A method for fast, computerized detection of bruises in magnetic resonance images (MRI) of apples was developed. It uses a simple thresholding technique combined with considerations of the apple geometry to distinguish between bright pixels representing the vascular system, and those representing bruises. The algorithm was tested on 20 images of ten Jonathan apples (before and after bruising), ten images of Golden Delicious apples and ten images of Hermon apples, and it demonstrated its ability to distinguish between bruised and non-bruised apples. This is the first step in the development of a sensing method using three-dimensional imaging and image analysis for detection of bruises.

Scientific Publication
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