A Binary SIFT Matching Method Combined with the Color and Exposure Information

2017 International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2017-04-01 DOI:10.1109/ICNISC.2017.00062

Mingzhe Su, Yan Ma, Xiangfen Zhang, Shun-bao Li, Yuping Zhang

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引用次数: 3

Abstract

The traditional SIFT method is capable of extracting distinctive feature for image matching. However, it is extremely time consuming in the SIFT matching due to the use of Euclidean distance measure. Recently, several binary SIFT (BSIFT) methods have been developed to improve the matching efficiency, whereas merely image brightness information is involved in these algorithms. The matching performance will drop because of the lack of the color information of the image. This paper presents a binary SIFT matching method combined with the color and exposure information. First, three components, including luminance, color offset and exposure offset are combined together to express the image pixel. Then, 128-D SIFT descriptor is converted into 256-bit binarized SIFT descriptor. Finally, the improved Hamming distance is proposed in the matching procedure. Experimental results on UKBench dataset show that the proposed method not only ensures the matching speed, but also improves matching accuracy.

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结合颜色和曝光信息的二值SIFT匹配方法

传统的SIFT方法能够提取出鲜明的特征进行图像匹配。然而，由于使用欧几里得距离度量，SIFT匹配非常耗时。近年来，为了提高匹配效率，人们开发了几种二值SIFT (BSIFT)算法，但这些算法只涉及图像亮度信息。由于缺少图像的颜色信息，匹配性能会下降。提出了一种结合颜色和曝光信息的二值SIFT匹配方法。首先，将亮度、色彩偏移和曝光偏移三个分量组合在一起表示图像像素;然后将128-D SIFT描述符转换为256位二值化SIFT描述符。最后，在匹配过程中提出了改进的汉明距离。在UKBench数据集上的实验结果表明，该方法不仅保证了匹配速度，而且提高了匹配精度。

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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2017 International Conference on Network and Information Systems for Computers (ICNISC)

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