A New Gradient-based Feature Extraction Method for Real-time Detection of Moving Objects Using Stereo Cameras

Authors

  • Güray Sonugür Department of Mechatronics Engineering, Faculty of Technology, Afyon Kocatepe University
  • Barış Gökçe Department of Mechatronics Engineering, Faculty of Engineering and Architecture, Necmettin Erbakan University

DOI:

https://doi.org/10.7546/CRABS.2022.03.11

Keywords:

digital cameras

Abstract

In this study, a gradient-based feature extraction method has been developed that can be used to detect moving objects in real-time applications such as unmanned ground or air vehicles. Feature extraction methods should produce fast results in real-time applications, as results need to be obtained between successive frames of video sequences within a limited time. For this reason, various sized image blocks were used in the developed method. The arithmetic mean (AM), geometric mean (GM), median (MD), and local contrast (LC) methods were used to calculate block intensities. In the stereo video stream, depth maps were also divided into blocks along with successive frames' R, G, and B channels. A novel feature extraction method was developed by calculating gradient-based relationships between adjacent blocks around the centre block. In experimental studies, the features extracted from stereo video frames using the proposed method were compared with Surf, Fast and Brisk methods according to their quantity, accuracy, and processing times, and more successful results were obtained. In addition, the moving object detection performance of the method was tested in real-time using an Unmanned Ground Vehicle. 

Author Biographies

Güray Sonugür, Department of Mechatronics Engineering, Faculty of Technology, Afyon Kocatepe University

Mailing Address:
Department of Mechatronics Engineering,
Faculty of Technology,
Afyon Kocatepe University
03200 Afyonkarahisar, Turkey

E-mail: gsonugur@aku.edu.tr

Barış Gökçe, Department of Mechatronics Engineering, Faculty of Engineering and Architecture, Necmettin Erbakan University

Mailing Address:
Department of Mechatronics Engineering
Faculty of Engineering and Architecture
Necmettin Erbakan University
42140 Konya, Turkey

E-mail: bgokce@erbakan.edu.tr

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Published

27-03-2022

How to Cite

[1]
G. Sonugür and B. Gökçe, “A New Gradient-based Feature Extraction Method for Real-time Detection of Moving Objects Using Stereo Cameras”, C. R. Acad. Bulg. Sci. , vol. 75, no. 3, pp. 414–421, Mar. 2022.

Issue

Section

Engineering Sciences