What Scikit-Image Meaning, Applications & Example
Image processing library for Python.
What is Scikit-Image?
Scikit-Image is an open-source Python library for image processing. Built on top of SciPy , it provides a collection of algorithms for image manipulation, including tasks like filtering, segmentation, geometric transformations, and feature extraction. It’s widely used in computer vision and image analysis projects due to its simplicity and powerful functionality.
Features of Scikit-Image
- Image Filtering: Apply various filters, such as Gaussian, median, and edge detection, to images.
- Segmentation: Tools for segmenting an image into regions based on color, intensity, or texture.
- Morphological Operations: Techniques like dilation and erosion for manipulating image shapes.
- Feature Extraction: Extract features like contours, regions, and object properties for further analysis.
Applications of Scikit-Image
- Medical Imaging: Used in processing medical scans for detecting anomalies or segmenting tissues.
- Object Detection : Helps in identifying and segmenting objects in images for recognition tasks.
- Satellite Image Analysis: Used to analyze and process aerial or satellite images for land use and environment monitoring.
Example of Scikit-Image
An example of using Scikit-Image is applying a Gaussian filter to an image to reduce noise:
from skimage import io, filters
# Load an image
image = io.imread('image.jpg')
# Apply Gaussian filter to reduce noise
filtered_image = filters.gaussian(image, sigma=1)