Image Processing Using Python

Overview

Python is a popular programming language for image processing due to its simplicity, ease of use, and availability of powerful libraries such as OpenCV and Pillow. Here is an overview of how to get started with image processing using Python: Installing Python and necessary libraries, Install OpenCV, Install Pillow, Loading and displaying an image, Import the necessary libraries, import Image, Load an image, Image manipulation, Convert an image to grayscale, Resizing an image, Image filtering and processing, Applying a Gaussian blur, Applying a threshold, Detecting edges, Saving an image. This is just a brief overview of image processing using Python. There are many other operations and techniques that can be applied to images using Python, and the libraries mentioned above offer a wide range of functionalities to explore.

Syllabus

Image Processing using Python

Week

Topic

Week 1:

Introduction to Python libraries for image processing, Basic image manipulation and enhancement techniques.

Week 2:

Advanced image manipulation and enhancement techniques, Geometric transformations, understanding image color spaces, Applying color manipulation techniques.

Week 3:

Understanding image histograms, applying image smoothing and sharpening techniques, understanding and applying basic and advanced image filtering techniques.

Week 4:

Image restoration techniques, Edge detection techniques, Feature extraction techniques.

Week 5:

Image segmentation, Thresholding techniques, Watershed segmentation.

Week 6:

Object detection and recognition, template matching, deep learning for image classification and recognition.

Week 7:

Image classification model with TensorFlow, Advanced deep learning models for medical image processing.

Week 8:

Preprocessing, Segmentation and Registration of medical images.

Week 9:

Understanding 3D image processing, image visualization and manipulation, filtering and segmentation.