360° IMAGE PROCESSING FOR AUTONOMIC ELECTRIC VEHICLE SURVEILLANCE APPLICATIONS

  • Yan Ario Eko Panca Manullang Universitas Nurtanio Bandung
  • Arief Suryadi Satyawan Badan Riset dan Inovasi Nasional
  • Ike Yuni Siswanti Universitas Nurtanio Bandung
Keywords: image fisheye, image processing greayscale kubus, RGB dan marcator.

Abstract

Surveillance serves to monitor the security of a camera-based area, therefore, the need for technology in the 4.0 era where technology is growing and increasingly sophisticated. Currently the development and availability of surveillance cameras with the need to cover a wider area, the need for clarity on the aspect of supervision is therefore made developments based on conventional cameras as 360° cameras. Some of the external factors that are difficult to avoid based on 360° cameras are distortion of the image and where this distortion refers to geometric distortion. Can cause the layout of the captured image information 360° camera distortion causes disinformation, there needs to be a solution based on these geometric deviations.

 

    In conclusion, after the Matlab program is run and works well using 360° image processing software using the Matlab programming language and the information can also be conveyed very clearly without reducing the function of the image based on the initial image. The suggestion is that every 360° image processing into a cube grayscale form and the marcator can be developed into realtime form, so that it can be applied directly to autonomous electric vehicles.

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References

Arief Suryadi SATYAWAN, 2019 Motion Estimation for Sequential Fisheye Images by Extending Optical Flow Concept (https://irdb.nii.ac.jp/en/00835/0004059274).

D. Scaramuzza, "Omnidirectional Camera," in Computer Vision: A Reference Guide, K. Ikeuchi, Ed., New York, Springer, pp. 552-560, Feb. 2016.

Davide Scaramuzza, Omnidirectional Camera GRASP Lab University of Pennsylvania.

Ikeuchi Katsui, 2014 Computer Guide Reference guide.

Farhan Utama, 2016 Pengembangan Perangkat Lunak Pemroses Gambar 360 Untuk Aplikasi Surveillance Sistem Di Bandara

Mai Xu, Senior Member, IEEE, Chen Li, Student Member, IEEE, Shanyi Zhang, Patrick Le Callet, Fellow, IEEE, 2015 State-of-the-art in 360° Video/Image Processing: Perception, Assessment and Compression.

Paul borke., 2004. Converting a fisheye image into a panoramic perspective projection.

Raquel Frizera Vassallo Lucas Frizera Encarnac¸ao Jose’ Santos-Victor Hans Jorg Schneebeli, 2014 BIRD’S EYE VIEW REMAPPING AND PATH FOLLOWING BASED ON OMNIDIRECTIONAL VISION.

Shree K. Nayar, Department of Computer Science, Columbia University New York, New York 10027 1997 Catadioptric Omnidirectional Camera.

S. Abraham and W. Forstner, "Fish-eye-stereo calibration and epipolar rectification," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 59, no.5, pp. 278-288, Aug. 2005.

Yanchang Wang, Xiaojin Gong, Ying Lin and Jilin Liu, 2014 Stereo Calibration and Rectification for Omnidirectional Multi-camera Systems.

Rofa, 2017 [Kunci Jawaban] Pelangi merupakan salah satu peristiwa yang menunjukkan bahwa cahaya memiliki sifat .... ~ ROFA Education Centre.

Jefferson Graham, 2015 Omnidirectional (360-degree) camera https://en.wikipedia.org/wiki/Omnidirectional_(360-degree)_camera.

MathWorks-Makers of MATLAB and Simulink-MATLAB https://www.mathworks.com/.

Published
2022-10-31
How to Cite
Manullang, Y. A. E. P., Satyawan, A. S., & Siswanti, I. Y. (2022). 360° IMAGE PROCESSING FOR AUTONOMIC ELECTRIC VEHICLE SURVEILLANCE APPLICATIONS. Prosiding Seminar Nasional Sains Teknologi Dan Inovasi Indonesia (SENASTINDO), 4, 408-414. https://doi.org/10.54706/senastindo.v4.2022.216

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