Automatic detection in a maritime environment: gradient filter versus intensity background estimation

Automatic detection of surface objects, like vessels, in a maritime environment from images is an important issue in naval surveillance. Two different approaches - gradient filter and background estimation - are presented in this paper and the test results on real data, both infrared as well as visible light images, are discussed. In the gradient approach, a gradient filter scans the sea-part of the image horizontally and vertically resulting in peaks at locations where the gradient exceeds a predefined local threshold. In the second approach, the background estimation, a polynomial model of the background is fitted locally to the seapart of the image. Using these polynomial background-estimators in the actual sea-analysis, objects are detected. In this paper the advantages and disadvantages of both approaches are discussed.