MARATTO

article · Journal of Real-Time Image Processing

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

2025Open accessSuez University

Abstract

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.

Research topics

  • Image Retrieval and Classification Techniques
  • Advanced Image and Video Retrieval Techniques
  • Anomaly Detection Techniques and Applications

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.1007/s11554-025-01705-y

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.