FPGA-based Object Detection and Classification of an Image

  • Abstract
  • Keywords
  • References
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  • Abstract

    Multi-core ARM processors built-in in new FPGA (Field Programmable Gate Array) devices are becoming common-place in recent years, and are used in Embedded systems in image and video processing applications.  Image detection and recognition applications such SIFT, BoF, and SVM algorithms written in python can be implemented in these devices.  In this study, a standalone FPGA-based system that detects and classifies objects in an image is presented. Linux Ubuntu operating system is configured on the FPGA board where it runs the object detection and classification algorithms implemented in python. Based on the results the system is able to detect and classify three categories of objects in an image.



  • Keywords

    FPGA; Object Detection; Object Classification; Object Association; Zedboard

  • References

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Article ID: 21784
DOI: 10.14419/ijet.v7i4.16.21784

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