Research on ship target detection method based on multi feature fusion
To avoid the problem of poor ship detection performance caused by complex ocean backgrounds,a ship tar-get detection method based on multi feature fusion is studied.Based on the selective search algorithm to obtain the initial po-tential area of the ship target,combined with geometric and grayscale feature constraints,the potential area of the ship target is selected.Texture,brightness,and contour features are extracted from the potential area of the ship target,and the adaptive fusion coefficient is used to fuse the multiple features of the ship target.The fusion result of the multiple features is used as input for the support vector machine classifier to achieve ship target detection.The experimental results show that this meth-od can effectively reduce the number of initial potential regions by more than 38％;By combining the ability to describe ship targets with multiple features,precise ship target detection can be achieved.
multi feature fusionship inspectiontexture featuresadaptive fusionsupport vector machine
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