摘要
该文分析了普通线性移不变边缘检测算子与人的视觉系统感知光强度变化时性能的不一致性，并根据视知觉原理提出了新的边缘检测模型和算法，由此所获得的边缘检测器不再仅是局部性的而且是兼备全局性的自适应特征提取系统．对一组含有小目标的自然场景图象的实验结果证实，与局部性算子相比，该方法具有优良的从低反差图象中提取边缘特征的性能．
The difference in the perception of light intensity variation between the human visual system (HVS) and commonly used linear and shift-invariant operators for edge detection is analyzed. Based on the principle of visual perception, a new model and an algorithm for detecting edges are proposed.. And the edge detector obtained is both a locally and globally adaptive system for feature extraction. The results of experiments on a set of images of outdoor scenes containing tiny objects show that, compared with local operators, the operator proposed exhibits excellent capability of extracting edge features from images with low contrast.
出处
《自动化学报》
EI
CSCD
北大核心
1994年第4期436-444,共9页
Acta Automatica Sinica
基金
国家自然科学基金
关键词
边缘检测
图象分割
模型
算法
edge detection
image segmentation
visual perception
object recognition
machine vision.
