摘要
从理论和试验两方面对归一化形态谱(形状谱)进行了分析和描述,同时证明了在采用圆盘状结构元素的情况下,归一化形态谱具有对图像的平移、旋转、缩放不敏感的特性,可以用作识别不同形状物体的特征参数。并且将归一化形态谱与人工神经网络相结合,实现了对机械工具产品的分类与识别,取得了很好的效果。
In this paper a normalized pattern spectrum is analyzed and described from theory and experiment. It also proves that this normalized pattern spectrum is provided with unready features for translation, rotation and zoom of images with disk structuring elements, and then the normalized pattern spectrum can be as recognition parameters of different shape objects. Integrating the pattern spectrum and artificial neural network, the classification and recognition of the series of mechanical tools are achieved, and the perfect effect is obtained.
出处
《新技术新工艺》
2006年第7期23-25,共3页
New Technology & New Process
基金
江苏省高校自然科学基金资助项目(03KJD46019399)