Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Biofouling detection based on image processing technique. / Grishkin, Valery; Iakushkin, Oleg; Stepenko, Nikolai.
11th International Conference on Computer Science and Information Technologies, CSIT 2017. ed. / Samvel Shoukourian. Vol. 2018-March Institute of Electrical and Electronics Engineers Inc., 2018. p. 158-161 (11th International Conference on Computer Science and Information Technologies, CSIT 2017; Vol. 2018-March).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Biofouling detection based on image processing technique
AU - Grishkin, Valery
AU - Iakushkin, Oleg
AU - Stepenko, Nikolai
PY - 2018/3/9
Y1 - 2018/3/9
N2 - Traditional methods for performing biofouling detection are based upon probing object surfaces for subsequent laboratory research. Such methods result in large effort, they are expensive, and require expert consultations. Knowledge of the type of biological contaminants is necessary to protect objects from their harmful impact. In this paper we propose a method for determination of types of biological contaminants existing on the objects surface. The proposed method uses a collection of object's images as input. The collection contains images obtained in the visible and near infrared spectral bands. During pre-processing the series, all images are converted to a selected shooting point, and the background is removed. Feature vector is built from combinations of formal vegetation indices. To recognize the type of biological contaminants, we used a pre-trained classifier based on SVM method with RBF kernel.
AB - Traditional methods for performing biofouling detection are based upon probing object surfaces for subsequent laboratory research. Such methods result in large effort, they are expensive, and require expert consultations. Knowledge of the type of biological contaminants is necessary to protect objects from their harmful impact. In this paper we propose a method for determination of types of biological contaminants existing on the objects surface. The proposed method uses a collection of object's images as input. The collection contains images obtained in the visible and near infrared spectral bands. During pre-processing the series, all images are converted to a selected shooting point, and the background is removed. Feature vector is built from combinations of formal vegetation indices. To recognize the type of biological contaminants, we used a pre-trained classifier based on SVM method with RBF kernel.
KW - biological fouling identification
KW - image processing
KW - pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=85050593788&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/biofouling-detection-based-image-processing-technique
U2 - 10.1109/CSITechnol.2017.8312162
DO - 10.1109/CSITechnol.2017.8312162
M3 - Conference contribution
AN - SCOPUS:85050593788
SN - 9781538628300
VL - 2018-March
T3 - 11th International Conference on Computer Science and Information Technologies, CSIT 2017
SP - 158
EP - 161
BT - 11th International Conference on Computer Science and Information Technologies, CSIT 2017
A2 - Shoukourian, Samvel
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Computer Science and Information Technologies, CSIT 2017
Y2 - 20 September 2017 through 25 September 2017
ER -
ID: 35949410