JRM Vol.35 No.1 pp. 153-159
doi: 10.20965/jrm.2023.p0153


Performance Evaluation of Image Registration for Map Images

Kazuma Kashiwabara*, Keisuke Kazama**, and Yoshitaka Marumo**

*Department of Mechanical Engineering, Graduate School of Industrial Technology, Nihon University
1-2-1 Izumi-cho, Narashino-shi, Chiba 275-8575, Japan

**Department of Mechanical Engineering, College of Industrial Technology, Nihon University
1-2-1 Izumi-cho, Narashino-shi, Chiba 275-8575, Japan

July 19, 2022
October 5, 2022
February 20, 2023
image registration, localization, image processing, computer vision, active safety

Safety must be guaranteed for the widespread use of automated vehicles. Accurate estimation of the automated vehicle’s self-position is crucial to guarantee the safety of the automated vehicle. In this study, the performance of an image registration method using brightness for the self-position estimation of automated vehicles using 2D map images was evaluated. Moreover, the effect of the difference between the two map images on the image registration was evaluated. Consequently, if a two-dimensional Fourier transform is applied to a map image and the brightness gradient feature is present in only one direction, image registration can be performed within a 15 pixels offset in that direction. In addition, image differences in the direction of no brightness gradient were difficult to align. If the brightness gradient is in more than two directions, image registration can be performed within a radius of 10 pixels. Furthermore, failure to align the images in the rotational direction significantly affected the alignment of the images. If a map image is transformed using a two-dimensional Fourier transform and there are multiple brightness gradient features, image registration using the brightness gradient is effective for the map image.

Image registration for map images

Image registration for map images

Cite this article as:
K. Kashiwabara, K. Kazama, and Y. Marumo, “Performance Evaluation of Image Registration for Map Images,” J. Robot. Mechatron., Vol.35 No.1, pp. 153-159, 2023.
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Last updated on Jul. 19, 2024