摘要
针对现有彩色图像的尺度不变特征转换(scale invariant feature transform,SIFT)算法计算复杂度较大和匹配性能较差的缺点,提出一种基于颜色量化矩阵的SIFT特征描述算法。首先由彩色图像的色调、饱和度和亮度生成颜色量化矩阵,然后由量化矩阵生成128维的SIFT特征描述子,最后应用于彩色目标匹配。实验结果表明,相比于现有彩色图像SIFT算法,本文方法具有匹配正确率高、匹配时间短和正确匹配点数多等优点,能够对彩色目标进行有效地匹配。
In order to avoid the disadvantages of huge computational complexity and poor matching performance in existing scale invariant feature transform（SIFT） descriptors for color images,a novel SIFT descriptor for color images based on color quantization matrix was given.The quantization matrix was obtained by triple-color components.And it was applied to generate a 128-dimensional SIFT descriptor to match color objects.The experimental results showed that,compared with existing SIFT descriptors for color images,this proposed method has the advantages of higher correct matching rate,less matching time and more accurate matching points.This method can effectively match the color objects.
出处
《山东大学学报（工学版）》
CAS
北大核心
2011年第2期46-50,共5页
Journal of Shandong University（Engineering Science）
基金
国家自然科学基金资助项目(61001179)
广东省自然科学基金资助项目(07301038
9451009001002667)
关键词
颜色量化矩阵
尺度不变特征转换(SIFT)
HSV颜色空间
特征匹配
color quantization matrix
scale invariant feature transform（SIFT）
hue saturation value（HSV） color space
feature matching
