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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:
Khalied Mohamed Hosny
Staff Zu Site
Abstract In Staff Site
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
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Khalied Mohamed Hosny, "Building a New Semantic Social Network Using Semantic Web-Based Techniques", ِASPG, 2021
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Khalied Mohamed Hosny, "New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework", IEEE, 2022
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Khalied Mohamed Hosny, "Fast computation of accurate Zernike moments", Springer, 2008
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Khalied Mohamed Hosny, "Accurate Computation of QPCET for Color Images in Different Coordinate Systems", SPIE, 2017
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Khalied Mohamed Hosny, "New optimized chaotic encryption with BCOVIDOA for efficient security of medical images in IoMT systems", Springer-Nature, 2024
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Hanaa Mohamed Hamza Kamal, "New optimized chaotic encryption with BCOVIDOA for efficient security of medical images in IoMT systems", Springer-Nature, 2024
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Asmaa Mohamed Khalid Mohamed Abbas, "New optimized chaotic encryption with BCOVIDOA for efficient security of medical images in IoMT systems", Springer-Nature, 2024
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Khalied Mohamed Hosny, "Improved model for intrusion detection in the Internet of Things", Springer-Nature, 2025
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