DOI

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.

Язык оригиналаанглийский
Название основной публикации11th International Conference on Computer Science and Information Technologies, CSIT 2017
РедакторыSamvel Shoukourian
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы158-161
Число страниц4
Том2018-March
ISBN (электронное издание)9781538628300
ISBN (печатное издание)9781538628300
DOI
СостояниеОпубликовано - 9 мар 2018
Событие11th International Conference on Computer Science and Information Technologies, CSIT 2017 - Yerevan, Армения
Продолжительность: 20 сен 201725 сен 2017

Серия публикаций

Название11th International Conference on Computer Science and Information Technologies, CSIT 2017
Том2018-March

конференция

конференция11th International Conference on Computer Science and Information Technologies, CSIT 2017
Страна/TерриторияАрмения
ГородYerevan
Период20/09/1725/09/17

    Предметные области Scopus

  • Компьютерные науки (разное)
  • Искусственный интеллект
  • Математика и теория расчета
  • Аппаратное обеспечение и архитектура ЭВМ
  • Информационные системы
  • Теория оптимизации

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