摘要
针对灰度,几何畸变较大的图像匹配困难的问题,提出了一种图像匹配的新方法。该方法在图像预处理时,首先利用SUSAN算法来检测图像目标的边缘,然后利用图像不变矩,并结合形态信息、灰度信息构造的图像综合特征来进行图像匹配,以完成目标的识别与跟踪。由于SUSAN算法检测特征定位准确,对局部噪声不敏感,而且不变矩具有平移、旋转、比例不变的特性,因此可取得较好的检测与匹配效果。实验也表明,该算法既具有较强的抗灰度、抗几何畸变能力,又具有较强的噪声抑制能力。
This paper describes a new approach to image matching. Edge detection uses SUSAN（Small Univalue Segment Assimilating Nucleus） method at low level image processing. Integration features matching can complete object recognition and tracking based on invariant moments in combination with configuration and intensity information. Feature detection with SUSAN method locates precisely and is not sensibly for local noise. Seven moments of image have translation invariant, rotation invariant and scale invariant. Simulations also show that the algorithm is efficient for image with intensity variety, geometry aberration and noise.
出处
《中国图象图形学报》
CSCD
北大核心
2007年第1期121-126,共6页
Journal of Image and Graphics
关键词
SUSAN算法
综合特征
不变矩
目标检测
匹配跟踪
SUSAN method, integration features, invariant moments, object detection, matching and tracking
