Odysseas Tsatos

  • Citations Per Year
Learn More
Support vector machines (SVMs) are powerful classifiers, with very good recognition rates in image analysis tasks. However their computational time in the object recognition phase is often large due to the number of classifications per scene and to the feature vector size, especially when the feature space is formed from raw image data. Several methods are(More)
Underwater images analysis is a difficult task due to their specific attributes: weak and variable lighting, low contrast, blurring. Therefore powerful image analysis algorithms, application specific, must be employed to obtain good results. In this paper we propose such a novel architecture based on a support vector machine (SVM) classifier, dedicated to(More)
Dams are very important economical and social structures that have a great impact on the population living in surrounding area. Dam surveillance is a complex process which involves data acquisition and analysis techniques, implying both measurements from sensors and transducers placed in the dam body and its surroundings, and also visual inspection. In(More)
Hydro-dams safety represents an important concern since their failure could be critical for the society. A key part of the hydro-dams surveillance programs is their visual inspection. However few computer vision support tools for implementing semi-automatically and objectively the visual surveillance and observation of the hydro-dams components exist. One(More)
Water resource management evaluation and planning is an important issue in the context of natural resources management, as it impacts the society, environment, ecology and economy. In the context of the information society, the development of comprehensive decision support components, with the capability of displaying the results of data processing in a(More)
  • 1