Scale Invariant Feature Transform Based Image Matching and Registration

H. Kher, V. Thakar
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引用次数: 17

Abstract

This paper presents Image matching and registration method that is invariant to scale, rotation, translation and illumination changes. The method is named as Scale Invariant Feature Transform (SIFT). This algorithm will detect and describe image features such as contours, points, corners etc. SIFT descriptors are the characteristic signature of the feature. The features calculated from the image to be registered should be distinctive and then it can be matched. It can be useful in object recognition, image mosaicing, 3 D reconstruction and video tracking. The simulation results shows that this algorithm works well in all types of cases having scale and rotation difference, it also register the object having occlusion and clutter background.
基于尺度不变特征变换的图像匹配与配准
提出了一种不受尺度、旋转、平移和光照变化影响的图像匹配配准方法。该方法被称为尺度不变特征变换(SIFT)。该算法将检测和描述图像的特征,如轮廓、点、角等。SIFT描述符是特征的特征签名。从待配准图像中计算出的特征必须具有显著性,才能进行匹配。它可以用于目标识别,图像拼接,三维重建和视频跟踪。仿真结果表明,该算法在具有尺度和旋转差异的各种情况下都能很好地实现对遮挡和杂波背景下目标的配准。
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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