Зміст курсу

Computer Vision Course Outline

1. Introduction to Computer Vision

What is Computer Vision?Fundamentals of Image Processing Linear algebra for image manipulation

2. Image Processing with OpenCV

Basic Transformations Fourier Transform Low-pass and High-pass Filters Noise Reduction and Smoothing Histogram Equalization Super-Resolution Techniques Edge Detection Corner and Blob Detection

3. Convolutional Neural Networks

Introduction to Convolutional Neural Networks Convolution Layers Pooling Layers Flattening Activation Functions Overview of Popular CNN Models

Edge Detection

Edges represent sudden changes in pixel intensity, which usually correspond to object boundaries. Detecting edges helps in shape recognition and segmentation.

Sobel Edge Detection

The Sobel operator calculates gradients (changes in intensity) in both the X and Y directions, helping detect horizontal and vertical edges.

Canny Edge Detection

The Canny Edge Detector is a multi-stage algorithm that provides more accurate edges by:

Applying Gaussian blur to remove noise.
Finding intensity gradients using Sobel filters.
Suppressing weak edges.
Using double thresholding and edge tracking.

A comparison of edge detection methods:

Завдання

Swipe to start coding

Your task is to apply both methods, Sobel and Canny. Steps:

Convert photo to grayscale;
Apply Sobel filter on X and Y directions with output depth cv2.CV_64F and kernel size 3;
Combine Sobel-filtered directions;
Apply a Canny filter with a threshold from 200 to 300.

Рішення

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 2. Розділ 7