摘要
本文提出一种用于实时图象跟踪的复杂环境下目标图象的自动分割方法,它可根据实际景物的变化适应性地交替使用基于景物复杂性分析的阈值分削和分层聚类分割两种工作方式,并尽可能抑制背景噪声的干扰。实验表明:本文所提方法的分割性能完全可与目前被认为是较为优越的几种实用分割方法相比,而在适应能力和可应用范围上它则明显优于后者,它的计算代价价通常也低于后者。
An automatic image segmentation method applied to real-time image tracking in complex environment is proposed. In accordance with the variance of scenes, this method can adaptively make alternate use of two work modes based of scene complexity: thresholding and hierarchically clustering. Meanwhile it suppresses the interruption of background noise as much as possible. Experimental results show that the presented approach is comparable in segmentation performances to several segmentation method currently considered as better ones, but its adaptability and usable range are much superior to, and its computing cost is usually lower than the latter.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1992年第1期54-60,共7页
Acta Electronica Sinica
关键词
图象
跟踪
分割
自适应处理
I mage tracking, Sequence image analysis, Segmentation, Adaptive processing, Guidance
