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General Information
Editor-in-chief
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2016 Vol.8(1): 58-62 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2016.V8.1020

Fast Image Diffusion for Feature Detection and Description

Lu Feng, Zhuangzhi Wu, and Xiang Long
Abstract—In this paper, we introduce a new multiscale 2D feature detection and description method based on optimal O(1) bilateral filter feature (OBFF). Existing methods detect and describe features by analyzing the scale space generated by linear and nonlinear diffusion kernel function, like Gaussian scale space and anisotropic diffusion scale space. By using the anisotropic diffusion scale space, KAZE features achieve significant progress on the 2D feature detection by using the anisotropic diffusion scale space. It makes the blurring locally adaptive and retains better feature localization accuracy and distinctiveness than the SIFT method. Our method OBFF also generates the nonlinear scale space of image to detect the local feature. The optimal bilateral filter is advantage in object boundary preserving and antinoise ability and dramatically speed up feature detection in nonlinear scale space. We use the benchmark datasets to compare our method with state-of-the-art approaches.

Index Terms—Bilateral filter, nonlinear scale space, feature detection, SIFT, binary descriptor.

The authors are with the Beihang University, Beijing, China (e-mail: fenglupeter@126.com, zzwu@buaa.edu.cn, long@buaa.edu.cn).

[PDF]

Cite:Lu Feng, Zhuangzhi Wu, and Xiang Long, "Fast Image Diffusion for Feature Detection and Description," International Journal of Computer Theory and Engineering vol. 8, no. 1, pp. 58-62, 2016.

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