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Estimating One-Dimensional Barcode Image Orientation by Using 2D Fourier Transform: A CPU-Based Approach

Can Ali Gülyurt1,
Sümer Erkan Kaya2
1Asis Automation and Fueling Systems Inc.
2Asis Automation and Fueling Systems Inc.
Published:May 31, 2024

Abstract

Barcode detection and decoding are critical tasks in numerous industrial sectors, including inventory management, logistics, and retail. Despite the advancements in Artificial Intelligence (AI) and Machine Learning (ML), many existing barcode detection methods rely heavily on GPU-accelerated techniques or are confined by specific angle requirements, limiting their versatility and computational efficiency. In this paper, a novel approach for stabilizing barcode image orientations using the 2D Fourier Transform was developed, with an emphasis on CPU-based implementation.

Keywords
Computer Vision2D Fourier TransformOne-Dimensional BarcodeOrientation Estimation

References

  1. 1.https://pypi.org/project/zbar/Link
  2. 2.https://www.arducam.com/product/arducam-full-hd-color-global-shutter-camera-for-raspberry-pi-2-3mp-ar0234-wide-angle-pivariety-camera-module-b0353/Link
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Cite This Article
Gülyurt, C. A., Kaya, S. E. (2024). Estimating One-Dimensional Barcode Image Orientation by Using 2D Fourier Transform: A CPU-Based Approach. *The European Journal of Research and Development*, 4(2), 199-205. https://doi.org/10.56038/ejrnd.v4i2.455

Bibliographic Info

JournalThe European Journal of Research and Development
Volume4
Issue2
Pages199–205
PublishedMay 31, 2024
eISSN2822-2296