LfePy: a Python package for local feature extraction with CPU and GPU compatibility

Faculty Computer Science Year: 2025
Type of Publication: ZU Hosted Pages: 1-14
Authors:
Journal: Journal of Real-Time Image Processing Springer-Nature Volume: 22
Keywords : LfePy: , Python package , local feature extraction    
Abstract:
Local features identify and describe distinct patterns or features in images at a localized level. However, extracting features from images is crucial for image analysis, as it enables models to acquire knowledge and identify patterns. Therefore, we introduce a novel Python package, LfePy (Local Feature Extractors for Python), that utilizes several local descriptors to extract features from grayscale images, ensuring compatibility with both Central Processing Units (CPUs) and Graphical Processing Units (GPUs). The package encompasses a range of techniques for addressing computer vision and image processing challenges. The LfePy package contains twenty-seven histogram-based descriptors and other essential image-processing methods. The package achieves a fast processing time for extracting features from images, as it includes a Graphical Processing Unit (GPU)-based version that outperforms related packages. This package is designed to advance the field of image analysis and related areas. It offers versatility, enhances performance, facilitates research, and supports a wide range of applications.
   
     
 
       

Author Related Publications

  • Khalied Mohamed Hosny, "SEMANTIC REPRESENTATION OF MUSIC DATABASE USING NEW ONTOLOGY-BASED SYSTEM", Journal of Theoretical and Applied Information Technology, 2020 More
  • Khalied Mohamed Hosny, "Building a New Semantic Social Network Using Semantic Web-Based Techniques", ِASPG, 2021 More
  • Khalied Mohamed Hosny, "New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework", IEEE, 2022 More
  • Khalied Mohamed Hosny, "Fast computation of accurate Zernike moments", Springer, 2008 More
  • Khalied Mohamed Hosny, "Accurate Computation of QPCET for Color Images in Different Coordinate Systems", SPIE, 2017 More

Department Related Publications

  • Khalied Mohamed Hosny, "New optimized chaotic encryption with BCOVIDOA for efficient security of medical images in IoMT systems", Springer-Nature, 2024 More
  • Hanaa Mohamed Hamza Kamal, "New optimized chaotic encryption with BCOVIDOA for efficient security of medical images in IoMT systems", Springer-Nature, 2024 More
  • Asmaa Mohamed Khalid Mohamed Abbas, "New optimized chaotic encryption with BCOVIDOA for efficient security of medical images in IoMT systems", Springer-Nature, 2024 More
  • Khalied Mohamed Hosny, "Improved model for intrusion detection in the Internet of Things", Springer-Nature, 2025 More
  • Khalied Mohamed Hosny, "A hybrid CNN and ensemble model for COVID-19 lung infection detection on chest CT scans", Plos, 2023 More
Tweet