Introduction

Introduction

Images play a crucial role in modern applications, from medical imaging to AI-driven object detection. Scikit-image is a Python library built on NumPy, designed for easy and efficient image processing. It provides a collection of algorithms for image manipulation, transformation, and analysis, making it a popular choice for researchers, data scientists, and developers working in the field of computer vision.

Purpose of scikit-image

The primary goal of scikit-image is to offer a well-structured and efficient image processing library that integrates seamlessly with the SciPy ecosystem. Some of its core purposes include:

• Ease of Use: Provides a user-friendly API with intuitive functions for image processing.

• Comprehensive Functionality: Includes a variety of operations such as filtering, segmentation, morphology, and feature detection.

• Performance Optimization: Built on NumPy arrays for efficient computation and optimized performance.

• Integration with Machine Learning: Often used as a preprocessing step in ML pipelines to prepare image data for training models.

• Open-Source & Actively Maintained: Community-driven with contributions from researchers and developers worldwide.