SIFT algorithm analysis and optimization

Zhu Daixian
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引用次数: 18

Abstract

Due to good invariance of scale, rotation, illumination, SIFT (Scale Invariant Feature Transform) descriptor is commonly used in image matching. The steps of extracting SIFT feature are analyzed in detail, and SIFT Key-point location is optimized. The Chamfer distance is used in this article; it decreases computation time and improves the accuracy of image matching. The experimental results show that the algorithm can reduce time complexity and maintain robust quality at the same time.
SIFT算法分析与优化
由于SIFT (scale Invariant Feature Transform,尺度不变特征变换)描述子具有良好的尺度、旋转、光照不变性,因此常用于图像匹配。详细分析了SIFT特征提取的步骤,优化了SIFT关键点的位置。本文采用倒角距离;它减少了计算时间,提高了图像匹配的精度。实验结果表明,该算法在降低时间复杂度的同时保持了鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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