Hardware implementation of bone fracture detector using fuzzy method along with local normalization technique

Abdullah-Al Nahid, Tariq M. Khan, Yinan Kong

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)

    Abstract

    Bone fracture detection from the digital image segmentation is a well-known image processing application which is frequently used to process biomedical images. Hardware realization of different image processing algorithm specially utilizing Field Programmable Gate Array (FPGA) has been gained a great interest among the researchers. FPGA has many significant features like spatial and temporal parallelism that best suits for real-time implementation of image processing. To gain the benefit from these characteristics of a FPGA, a new method for bone fracture detection is proposed and its performance is validated through real-time implementation. Simulation results show that the proposed method give superior performance than the existing method.
    Original languageEnglish
    Pages (from-to)533-546
    Number of pages14
    JournalAnnals of Data Science
    Volume4
    Issue number4
    Early online date21 Jul 2017
    DOIs
    Publication statusPublished - Dec 2017

    Keywords

    • bone fracture
    • canny
    • fuzzy
    • FPGA
    • normalization

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