For the influence of some complex sea states such as coastal scenery and surface ripple in sea images,target detection based on the visible light image is a technical difficult problem of the current.This paper presents a method of structured random forests for target detection in sea images.The method first constructs random decision forest based on image block,applies structured learning strategy to the forecast output spatial of the constructed random decision forest,and then trains the random decision forest in the sample space,and finally classifies the testing image blocks as the target region and the background region through random decision forest.The experimental results show that compared with the Canny operator,the Threshold-Segment operator,and the Salience_ROI operator,the method of this paper has significant advantages in the aspects of sea image target detection and uses low computation cost.