区域高斯描绘子及其在物体识别中的应用  

Regional Gaussian descriptors and their application to object recognition

作　　者：刘亦书[1] 

机构地区：[1]华南师范大学地理科学学院,广东广州510631

出　　处：《计算机工程与设计》2007年第15期3650-3651,3655,共3页Computer Engineering and Design

基　　金：广东省自然科学基金博士启动项目(04300033)

摘　　要：为了对几何变形的图像进行正确和有效的识别,对基于物体轮廓的高斯描绘子进行推广,构造了一种基于区域的新的不变量——区域高斯描绘子。构造思路主要有两点:①定义一个具有平移、尺度不变性的函数——区域高斯势函数;②分别计算区域高斯势函数在8个同心圆上的平均值,从而获得8个不变量。这些不变量不仅具有平移、旋转、尺度和反射不变性,而且对噪声不敏感,适用范围广。将区域高斯描绘子应用于物体识别,获得很高的识别率。Feature extraction is a challenging problem in the field of pattern recognition. Features mainly fall into two classes： boundary descriptors and regional descriptors. Gaussian descriptors, which have attractive properties and show promising performance, belong to the former class. This paper is an improvement and an extension of Gaussian descriptors. A series of novel invariants called regional Gaussian descriptors are constructed based on region. The method includes defining a regional Gaussian potential function （RGPF） and then constructing 8 regional Gaussian descriptors by calculating the averages of RGPF＇s along 8 circles with the same center. Some properties of regional Gaussian descriptors including the invariance on translation, rotation, scaling changes and reflection are studied. A central advantage of these new features over Gaussian descriptors is that they are insensitive to noise and edge variations. To support our new theory, an algorithm for object recognition is designed based on regional Gaussian descriptors and numerical experiments are conducted, and experiment results give an encouraging high recognition rate.

关 键 词：高斯势函数 高斯描绘子 区域高斯描绘子 不变量 物体识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]