To solve the problem that it is difficult to directly detect the object in the water due to flares and cloud shadows

this paper proposed a water wake recognition method based on Multi-Channel Gabor filters

and BP neural network. First

we select sample sub-images of same sizes with wake texture and without wake texture

then

we obtain feature images using a group of Gabor filters and calculate the mean and variance of feature images to acquive

the input vectors and train the BP network. Secondly we divide the whole image into sub-images with the same size as the first step

calculate mean and variance of Gabor feature images

caculate the input vector and judge whether the sub-image contain a wake texture by the trained BP network in the first step. We obtain a binary image by the classify results of the whole image

detect lines using Hough transform and judge whether there is a wake in the whole image. From experiment results

it is proved that the proposed algorithm can attain the wake texture precisely.