Image Processing with Python

1. Introduction

• In today's digital age, image processing has become an important part of many technology applications, from facial recognition to medical image processing. OpenCV, a leading open source library in the field, provides a series of powerful tools for easy and efficient image processing and analysis.
• This project will introduce how to use OpenCV to process images using the Python programming language. We will learn how to use OpenCV's basic functions to perform operations such as image transformation, image filtering, histogram calculation, and basic geometric transformations.

2. Abstract

• The image processing focused project will focus on using the OpenCV library with the Python programming language to perform a series of basic exercises related to image processing.There are also simple instructions for recording and reading videos in real time.
  • Exercises on image processing
    • Add Image Noise
      • Gaussian noise
      • Salt and Pepper Noise
    • Add watermark
    • Cointour Detection
    • Collage Image
    • Combined Image
    • Contour Image
    • Emboss image
    • Erosion and Dilation
    • Feature Mapping Image
    • Basic image processing with OpenCV
    • Remove Background
    • Remove image noise
      • Gaussian noise
      • Salt and Pepper Noise
    • Sharpen Image
    • Sketch Image
    • Vignette filter
  • Exercises on video processing
    • Read video from webcam displayed with three windows in real time
      • "Original Video" window: Displays the original video with the original color of each frame.
      • "Black and White Video" window: Displays the video with each frame converted to black and white.
      • "Video Edges" window: Displays the video with each frame converted to black and white and then edges detected using the Canny method.

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