一种基于支持向量机的三维物体识别方法.doc

一种基于支持向量机的三维物体识别方法*
徐胜彭启琮管庆赵明渊
(电子科技大学通信与信息工程学院, 成都 610054)
摘要: 提出从三维物体的二维图像中提取仿射不变傅氏描述子、色彩矩及纹理特征, 组成一个25维的特征向量, 送入支持向量机训练并用于三维物体识别。算法利用了仿射不变傅氏描述子在物体发生仿射形变时具有不变性, 利用色彩矩和纹理特征区分形状相似但有不同颜色及纹理的物体, 并引入支持向量机作为分类器。基于三维物体图像数据库COIL-100测试了算法的识别性能, 当每个物体训练样本图像数量为36个(视角间隔10°)时达到了100%的识别率, 进一步减少训练视角数量也达到较满意的识别性能。
关键词: 三维物体识别;仿射不变傅氏描述子;色彩矩;纹理分析;支持向量机
中图分类号: 文献标识码: A 国家标准学科分类代码:
A method for 3-d object recognition based on support vector machine
Xu Sheng Peng Qicong Guan Qing Zhao Mingyuan
(School munication and Information Engineering, Univ. of Electron. Sci. & Tech. of China, Chengdu 610054, China)
Abstract: To improve the performance of 3D objects recognition system, a method is proposed to extract the affine-invariant Fourier descriptors (AIFD), color moments and texture features from the 2D images of 3D objects. These features bined into a feature vector of ponents and sent to support vector machines for training and recognition. The invariance properties of AIFD under affine transformation (translation, scaling, rotation and shearing) for an object are used in this method. And color moment and texture features are used to distinguish the object of similar shape and different appearance. Support vector machines are used as classifier. Based on the public 3D objects dataset COIL-100 the method was assessed. 100% correct rate of recognition is achieved when the nu