关键词: 异源图像, 目标检测, 评价向量, k-means聚类

Abstract: How to evaluate the reliabilities of different image sensors and their processing result is an important issue in the field of multi-modal objects detection. As single-source sensor in object detection has the disadvantages of high miss rate and mistake rate, this paper proposes a new approach, which can evaluate the reliabilities of the detection results in different source images. Firstly, three evaluation factors of inertia, target number of inertia and target independent integrity are introduced to construct an evaluation vector to assess the quality of motion detection. Secondly, k-means clustering are used to generate the target center vector. Then the cooperative and competitive mechanism are applied to feedback the clustering similarity. Finally, the objects detection in different source images is realized. Simulations on lots of images verify that the new proposed approach is more robust for lower detection error rate and false-negative rate.

Key words: different source images, objects detection, evaluation vector, k-means clustering