Description

TABLE OF CONTENT

1 . Introduction to Image Processing

Overview of Image Processing
Importance and Applications

2 . Basics of Python for Image Processing

Python Programming Fundamentals
Libraries for Image Processing (e.g., NumPy, OpenCV)

3 . Image Representation and Manipulation

Understanding Image Pixels
Image Types (RGB, Grayscale, Binary)
Basic Image Operations

4 . Image Filtering and Enhancement

Convolution and Filters
Blurring and Sharpening
Histogram Equalization

5 . Image Transformation and Geometric Operations

Image Rotation, Translation, and Scaling
Affine and Perspective Transformations

6 . Color Spaces and Channels

RGB, HSV, CMYK
Extracting and Manipulating Color Channels

7 . Feature Extraction and Object Detection

Edge Detection (Sobel, Canny)
Corner Detection (Harris Corner Detection)
Object Detection Techniques

8 . Image Segmentation

Thresholding
Region-based Segmentation
Watershed Algorithm

9. Image Compression

Introduction to Compression
Lossless and Lossy Compression
JPEG and PNG Compression

10 . Deep Learning for Image Processing

Introduction to Neural Networks
Convolutional Neural Networks (CNNs)
Transfer Learning for Image Classification

11 . Image Restoration

Noise Reduction Techniques
Image Denoising Algorithms