Target Detection Method in Multimodal Images with Complex Backgrounds and Different Views

Target detection in multimodal (multisensor) images is a difficult problem especially with the impact of different views and the complex backgrounds. In this paper, we propose a target detection method based on ground region matching and spatial constraints to solve it. First, the extrinsic parameters of camera are used to transform the images to reduce the impact of viewpoints differences. Then the stable ground object regions are extracted by MSER. Those regions are used to build a graph model to describe the reference image with spatial constraints to reduce the impact of multimodal and complex backgrounds. At last, the ground region matching and the model registration with sensed images are used to find the target. Using this method, we overcome those difficulties and obtain a satisfied experiment result; the final detection rate is 94.34% in our data set of visible reference images in top views and infrared sensed images in side views