Abstract

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.

Original languageEnglish
Title of host publication11th International Conference on Computer Science and Information Technologies, CSIT 2017
EditorsSamvel Shoukourian
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages158-161
Number of pages4
Volume2018-March
ISBN (Electronic)9781538628300
DOIs
Publication statusPublished - 9 Mar 2018
Event11th International Conference on Computer Science and Information Technologies, CSIT 2017 - Yerevan
Duration: 20 Sep 201725 Sep 2017

Conference

Conference11th International Conference on Computer Science and Information Technologies, CSIT 2017
CountryArmenia
CityYerevan
Period20/09/1725/09/17

Fingerprint

Biofouling
Image Processing
Image processing
Impurities
Research laboratories
Classifiers
Vegetation Index
Shooting
Infrared radiation
Feature Vector
Preprocessing
Processing
Infrared
Classifier
kernel
Necessary
Series
Object

Scopus subject areas

  • Computer Science (miscellaneous)
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Hardware and Architecture
  • Information Systems
  • Control and Optimization

Cite this

Grishkin, V., Iakushkin, O., & Stepenko, N. (2018). Biofouling detection based on image processing technique. In S. Shoukourian (Ed.), 11th International Conference on Computer Science and Information Technologies, CSIT 2017 (Vol. 2018-March, pp. 158-161). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSITechnol.2017.8312162
Grishkin, Valery ; Iakushkin, Oleg ; Stepenko, Nikolai. / Biofouling detection based on image processing technique. 11th International Conference on Computer Science and Information Technologies, CSIT 2017. editor / Samvel Shoukourian. Vol. 2018-March Institute of Electrical and Electronics Engineers Inc., 2018. pp. 158-161
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title = "Biofouling detection based on image processing technique",
abstract = "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.",
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author = "Valery Grishkin and Oleg Iakushkin and Nikolai Stepenko",
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Grishkin, V, Iakushkin, O & Stepenko, N 2018, Biofouling detection based on image processing technique. in S Shoukourian (ed.), 11th International Conference on Computer Science and Information Technologies, CSIT 2017. vol. 2018-March, Institute of Electrical and Electronics Engineers Inc., pp. 158-161, Yerevan, 20/09/17. https://doi.org/10.1109/CSITechnol.2017.8312162

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.

Research output

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

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VL - 2018-March

SP - 158

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BT - 11th International Conference on Computer Science and Information Technologies, CSIT 2017

A2 - Shoukourian, Samvel

PB - Institute of Electrical and Electronics Engineers Inc.

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Grishkin V, Iakushkin O, Stepenko N. Biofouling detection based on image processing technique. In Shoukourian S, editor, 11th International Conference on Computer Science and Information Technologies, CSIT 2017. Vol. 2018-March. Institute of Electrical and Electronics Engineers Inc. 2018. p. 158-161 https://doi.org/10.1109/CSITechnol.2017.8312162