Performance Evaluation of Image Registration for Map Images

Author:

Kashiwabara Kazuma1,Kazama Keisuke2,Marumo Yoshitaka2

Affiliation:

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

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

Abstract

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.

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

Reference28 articles.

1. Japan Automobile Manufactures Association, Inc., AD Safety Evaluation Subcommittee, “Safety Assessment Framework for Automated Driving Ver1.0,” 2021 (in Japanese).

2. ITS and Automated Driving Promotion Office, Automobile Division, Manufacturing Industries Bureau, Ministry of Economy, Trade and Industry, “Automatic Driving Business Study Group / 3rd Meeting of Safety Evaluation Strategy WG Agenda,” 2021 (in Japanese).

3. Bundesministerium für Wirtschaft und Energie, “PEGASUS METHOD An Overview,” 2019.

4. H. Nakanishi, “Navigation and Guidance Control of Mobile Objects Using GPS – Application to Rescue Robots (< Special Issue > Mathematics and Applications of GPS/GNSS Positioning),” Systems, Control and Information, Vol.51, No.6, pp. 279-284, 2007 (in Japanese).

5. P. Xie and M. G. Petovello, “Measuring GNSS Multipath Distributions in Urban Canyon Environments,” IEEE Trans. on Instrumentation and Measurement, Vol.64, No2, pp. 366-377, 2015.

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