摘要
对于一幅观察到的图像,其特征不仅包含几何结构,而且可能包含纹理或者噪声。图像特征的分类与分割在图像处理和图像识别领域中起到重要作用(如去噪、边缘检测和纹理分割)。本文从函数空间和频域变换的角度,介绍图像特征描述方法现状,并进行比较,总结各自的优缺点,最后给出图像特征目前研究的应用领域。
An observed image which is characterized not only contains the geometric structure, but also may contain noise or tex- ture. Image feature classification and segmentation play an important role in the fields of image processing and pattern recognition （such as de-noising, edge detection and texture segmentation）. From the function space and frequency-domain transformation, this paper introduces the represent methods of image feature and compares it, summarizes the advantages and disadvantages of each. At the end, the application area of image feature study is given in personal opinion.
出处
《计算机与现代化》
2013年第5期80-86,94,共8页
Computer and Modernization
基金
中国高等教育学会"十二五"教育科学规划(11YB071)
江苏省"十二五"现代教育技术研究所立项课题(2011-R-19502)
关键词
图像特征
函数空间
有界变差
小波变换
曲波变换
image feature
function space
bounded variation
wavelet transform
contourlet transform
