Fractal-based Detection of Objects in Underwater Images
基于分形的水声图像目标探测

Considering the problem of detecting artifacts in underwater images, a fractal-based algorithm is proposed in this paper. Because the fractal model differs greatly from man-made objects but perfectly approximates the natural objects, so the algorithm based on fractal models could accurately distinguish the artifacts from natural backgrounds. The definitions and calculations of fractal dimension are discussed in this paper. The underwater images are registered as artifacts regions and non-artifacts regions by thresholding based on the fractal features. This fractal-based object detection is applied to some noisy underwater images and the corresponding detection results are presented in this paper. The experimental results indicated that the fractal features are fit for the classification of artifacts and natural backgrounds, and have somewhat low sensitivity to the Gaussian noise. So the fractal-based algorithm is appropriate to detecting the artifacts in underwater images that are often contaminated.