The multi-target segmentation in complex background could be solved effectively by synthetically utilizing multi-sensor images’ gray level distribution, fractal dimension and active contour evolution technology. Firstly, according to image inherent attribution, the images were enhanced using the histogram specification. Then the regions of interest were selected in multi-sensor images by using fractal dimension features for visible images, maximum entropy method for infrared images and the local threshold for Lidar images. The regions-of-interest obtained in multi-sensor images were across verified, so background clutter could be further eliminated. Finally, the target contour estimation could be used as the initial growth curve for active contour evolution processing, and the better target contours were obtained on the true target boundaries. A large number of segmentation tests on multi-sensor images in complex scenes prove the validity and reliability of the scheme.