Programmable Architectures for Histogram of Oriented Gradients Processing

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)


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    There is an increasing demand for high performance image processing platforms based on field programmable gate array (FPGA). The Histogram of Orientated Gradients (HOG) algorithm is a feature descriptor algorithm used in object detection for many security applications. The chapter examines the implementation of this key algorithm using an FPGA-based soft-core architecture approach. Firstly, the HOG algorithm is described and its performance profiled from a computation and bandwidth perspective. Then the IPPro soft-core processor architecture is introduced and a number of mapping strategies are covered. A HOG implementation is demonstrated on a Zynq platform, resulting in a design operating at 15.36 fps; this compares favorably with the performance and resources of handcrafted VHDL code.
    Original languageEnglish
    Title of host publicationHandbook of Signal Processing Systems
    Pages649 - 682
    Number of pages33
    ISBN (Electronic)978-3-319-91734-4
    Publication statusPublished - 2019

    Research outputs

    ID: 160984848