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אסיף מאגר המחקר החקלאי
פותח על ידי קלירמאש פתרונות בע"מ -
In-vivo fish sorting by computer vision
Year:
2000
Source of publication :
Aquacultural Engineering
Authors :
ציון, בועז
;
.
קרפלוס, אילן
;
.
שקליאר, אלכסנדר
;
.
Volume :
22
Co-Authors:
Zion, B., Inst. of Agricultural Engineering, Agric. Res. Org., Volcani Ctr., P., Bet Dagan, Israel
Shklyar, A., Inst. of Agricultural Engineering, Agric. Res. Org., Volcani Ctr., P., Bet Dagan, Israel
Karplus, I., Department of Aquaculture, Agric. Res. Org., Volcani Ctr., P., Bet Dagan, Israel
Facilitators :
From page:
165
To page:
179
(
Total pages:
15
)
Abstract:
An image-processing algorithm, applied to images of common carp (Cyprinus carpio), St. Peter's fish (Oreochromis sp.) and grey mullet (Mugil cephalus), successfully discriminated among the species. Fish images were acquired while they were swimming in an aquarium with their side to the camera. The algorithm was based on the method of moment-invariants (MI) coupled with geometrical considerations and was, therefore, insensitive to fish size, two-dimensional orientation and location in the camera's field of view. One hundred and forty three images (47 grey mullet, 43 St. Peter's fish and 53 carp images) were acquired and divided into two sets: 20 grey mullet, 20 St. Peter's fish and 20 carp images in one set and the rest of the images in the other set. Each of these two sets was used as a training set for selection of feature thresholds, which were then applied to the other set as a test case (two-fold cross-validation test). Fish species identification reached 100, 91 and 91% for grey mullet, carp and St. Peter's fish, respectively. To the best of our knowledge this is the first report on successful discrimination among fish species in vivo. We also report the results of a preliminary experiment, conducted to test the capability of fish to be trained to swim through a narrow Plexiglas channel which could be part of a sorting system, and through which fish images could possibly be acquired. (C) 2000 Elsevier Science B.V.
Note:
Related Files :
computer vision
Cyprinus carpio
Fish species
In vivo
Oreochromis
עוד תגיות
תוכן קשור
More details
DOI :
10.1016/S0144-8609(99)00037-0
Article number:
0
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
19272
Last updated date:
02/03/2022 17:27
Creation date:
16/04/2018 23:27
Scientific Publication
In-vivo fish sorting by computer vision
22
Zion, B., Inst. of Agricultural Engineering, Agric. Res. Org., Volcani Ctr., P., Bet Dagan, Israel
Shklyar, A., Inst. of Agricultural Engineering, Agric. Res. Org., Volcani Ctr., P., Bet Dagan, Israel
Karplus, I., Department of Aquaculture, Agric. Res. Org., Volcani Ctr., P., Bet Dagan, Israel
In-vivo fish sorting by computer vision
An image-processing algorithm, applied to images of common carp (Cyprinus carpio), St. Peter's fish (Oreochromis sp.) and grey mullet (Mugil cephalus), successfully discriminated among the species. Fish images were acquired while they were swimming in an aquarium with their side to the camera. The algorithm was based on the method of moment-invariants (MI) coupled with geometrical considerations and was, therefore, insensitive to fish size, two-dimensional orientation and location in the camera's field of view. One hundred and forty three images (47 grey mullet, 43 St. Peter's fish and 53 carp images) were acquired and divided into two sets: 20 grey mullet, 20 St. Peter's fish and 20 carp images in one set and the rest of the images in the other set. Each of these two sets was used as a training set for selection of feature thresholds, which were then applied to the other set as a test case (two-fold cross-validation test). Fish species identification reached 100, 91 and 91% for grey mullet, carp and St. Peter's fish, respectively. To the best of our knowledge this is the first report on successful discrimination among fish species in vivo. We also report the results of a preliminary experiment, conducted to test the capability of fish to be trained to swim through a narrow Plexiglas channel which could be part of a sorting system, and through which fish images could possibly be acquired. (C) 2000 Elsevier Science B.V.
Scientific Publication
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