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一种改进的多尺度Harris角点检测算法
引用本文:朱士杰,马峻.一种改进的多尺度Harris角点检测算法[J].电脑开发与应用,2010,23(6):31-33.
作者姓名:朱士杰  马峻
作者单位:太原科技大学系统仿真与计算机应用研究所,太原,030024
摘    要:传统角点检测算法对尺度很敏感,而且提取角点是像素级的。采用图像增强技术,通过DOG算子将多尺度运用到Harris算法中,然后除去极值点附近低对比度的特征点。不仅避免了传统灰度变换技术的单一性,还提高了增强处理后图像的稳定性。改进的多尺度Harris角点检测方法具有误差较小、伪角点较少、错误率较低、匹配精度性较高等特点。

关 键 词:角点检测  多尺度  DOG算子  高斯金字塔  图像增强

An Improved Multi-scale Harris Corner Detection Algorithm
Abstract:Traditional corner detection algorithm is very sensitive to scale, and extract the corner point is the pixel-level. Using image enhancement technology, Through the DOG operator will be applied to the multi-scale Harris algorithm, Then remove the extreme point of the feature points near the low-contrast, To avoid the traditional gray-scale transformation technology singularity, Improved to enhance the stability of processed images. Experimental results show that the improved multi-scale Harris corner detection method has the charateristic of smaller error, pseudo-corner point less, error rate lower and the markedly improved accuracy and soon.
Keywords:corner detection  multi-scale  DOG operator  DOG pyramid  image enhancement
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