摘要
基于B-样条小波计算边缘曲线多尺度曲率函数,根据多尺度信息筛选和定位超过一定曲率阀值的犄角点,这样的点代表了边缘曲线的主要信息.文中使用了Canny边缘检测算子和数学形态学方法进行图像预处理,B-样条小波降低对噪声及扰动的灵敏性,以提高真实犄角点定位水平.综合[1,2]给出新的角特征矢量,并生成角点特征序列CS和弧段特征序列SS.特征序列可作为自适应-时滞单元混合神经网络的输入,通过学习完成图像分类与识别,对基于植物叶片形状识别种类提供辅助.
In this paper, based on B-spline wavelets multiscale curvature functions of image edges are calculated. By the multiscale curvature corners with important informations are filtered and located whose values are over a threshold. Some technologies, Canny edge detecting operating and Mathematical morphology are employed for image preprocessing and B-spline wavelets are employed for reducing the effect of noise or small variation, which brings us benefits to locate corner points with high accuracy . Basing on [1, 2] new corner feature vetor were given , and by which corner feature series CS and curve segment feature series SS are constructed. The numerical features can be as an input dataset of Adaptive-Delay Cell Hybrid Neural Network(ADCHNN), and image classification and recognition can be accomplished by learning. The work will give great help for plant identification by their leaf shape.
出处
《生物数学学报》
CSCD
2003年第4期461-466,共6页
Journal of Biomathematics
基金
中国科学院知识创新工程重大方向项目:微波遥感信息特征及目标特性研究(KZCX2-309)
国家自然科学基金(19471006)
