计算机工程与应用2019，Vol.55Issue(1)：180-185,270,7.DOI:10.3778/j.issn.1002-8331.1709-0418
基于评价向量的异源图像目标检测
Objects Detection in Different Source Images Based on Evaluation Vector
摘要
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.关键词
异源图像/目标检测/评价向量/k-means聚类Key words
different source images/objects detection/evaluation vector/k-means clustering分类
信息技术与安全科学引用本文复制引用
郗润平,贾高云,张艳宁,张福俊..基于评价向量的异源图像目标检测[J].计算机工程与应用,2019,55(1):180-185,270,7.基金项目
国家自然科学基金(No.61572405,No.61231016,No.61303123) （No.61572405,No.61231016,No.61303123）
国家高技术研究发展计划(863)(No.2015AA016402) （863）
模式识别国家重点实验室开放课题(No.201600038). （No.201600038）
