摘要
图像分割是自动目标识别系统（ＡＴＲＳ）的关键部分，它是一种基本的图像分析技术，作为图像分析的重要步骤在许多图像应用分析中都是必不可少的，其目的是将目标和背景分离，为目标识别、精确定位等后序处理提供依据，其结果直接影响到其后的信息处理过程。评估分割算法的性能是ＡＴＲＳ离线评估的重要组成之一。根据运筹学与系统工程思想、提出了一种基于灰色关联度分析的图像分割性能评估方法。该方法综合灰色系统理论和层次分析法等新兴学科的精华，有机结合而成。文中介绍了该方法的基本原理，并对其合理性做了理论分析，给出了同以往方法的实验对比结果，应用实例显示，它在分割算法的性能评估方面比其它的一些方法更为有效、合理。在现有文献基础上提高了数据的离散性，便于区分不同分割算法的性能，较好地克服了以往评估方法的不灵敏性和奇异性，从而使评判更容易进行。
Abstract Image segmentation is the key component in automatic target recognition systems (ATRS). Its an important step of image analysis. Its results have critical implications for the information processing stragies that follow. The evaluation of a segmentation algorithm takes an important role in the estimation of performance for an off\|line ATRS. The comprehensive evaluation model, a new idea and way to comprehensive evaluate image segmentation is discussed. A model of grey systems appraise combining grey appraise method with the Analytic Hierarchy Process (AHP) is proposed in this paper, it is used to evaluate the performance of image segmentation. The evaluation models and their experimental comparative results are also discussed to prove its feasibility, and to confirm the advantages of this new method. Its application shows that the new method is more effective and more scientific reasonable than other methods.
出处
《红外与激光工程》
EI
CSCD
1999年第3期19-23,共5页
Infrared and Laser Engineering
基金
国家自然科学基金
