尺度不变特征变换算子综述

刘立; 詹茵茵; 罗扬; 刘朝晖; 彭复员

doi:10.11834/jig.20130801

综述 | 浏览量 : 0 下载量: 456 CSCD: 0

PDF
导出
分享
收藏
专辑

尺度不变特征变换算子综述
Summarization of the scale invariant feature transform
2013年18卷第8期页码：885-892
纸质出版：2013
DOI： 10.11834/jig.20130801
稿件说明：

移动端阅览

刘立, 詹茵茵, 罗扬, 刘朝晖, 彭复员. 尺度不变特征变换算子综述[J]. 中国图象图形学报, 2013,18(8):885-892. DOI： 10.11834/jig.20130801.

Liu Li, Zhan Yinyin, Luo Yang, Liu Chaohui, Peng Fuyuan. Summarization of the scale invariant feature transform[J]. Journal of Image and Graphics, 2013, 18(8): 885-892. DOI： 10.11834/jig.20130801.

摘要

随着计算机软件与硬件技术的发展

计算机视觉算法逐渐成为图像处理领域的研究热点。其中SIFT(scale invariant feature transform)算法是目前机器视觉领域应用最成功的算法之一。由于在尺度不变、旋转不变、光照不变等方面的独特优势

SIFT被广大视觉领域的研究者借鉴与学习。但是SIFT算法本身也存在一些问题

如仿射性能不太理想

计算复杂度过高等

因此针对它的多种改进算法不断出现。本文对SIFT的发展历史、SIFT算法的演变以及它不同领域的典型应用给出了一个比较全面的综述

比较了各类算法的优缺点。最后给出了该算法未来可能的发展方向

为视觉研究者提供参考。

Abstract

With the development of software and hardware technique

computer vision has become a hot research fields in image processing. Scale invariant feature transform (SIFT) is one of the most successful vision algorithm nowadays and it is widely studied by the computer vision community because of its unique features.SIFT is scale invariant

rotation invariant and illumination invariant. However

it also has some problems such as it is only part affine has a rather the high computation complexity. Many extended or modified algorithms of the SIFT are developed unceasingly. In this paper

we summarize the history

the evolved processing

and the application of the SIFT and compares those algorithm effects. At last

the paper discusses the feature direction and provides reference for computer vision researchers.