Cany Edge Detetcor

TABLE OF CONTENTS

1. Introduction

- Problem Statement

- Overview of Canny Edge Detection

- Objectives of the Implementation

2. Grayscale Conversion

- Importance of Grayscale Conversion in Edge Detection

- Methodology for Converting RGB to Grayscale

- Code Implementation

3. Gaussian Blur

- Role of Gaussian Blur in Noise Reduction

- Explanation of Gaussian Kernel

- Manual Implementation of Gaussian Kernel

- Convolution Process

- Code Implementation

4. Gradient Calculation

- Importance of Gradient Calculation

- Explanation of Intensity Gradients

- Calculation of Gradient Magnitude and Direction

- Use of Sobel Filters for Gradient Calculation

- Code Implementation

5. Non-Maximum Suppression

- Purpose of Non-Maximum Suppression

- Methodology for Thinning Edges

- Suppressing Non-Maximum Pixels

- Code Implementation

6. Double Thresholding

- Role of Thresholding in Edge Detection

- Explanation of Strong, Weak, and Non-Relevant Pixels

- Selection of High and Low Threshold Values

- Code Implementation

7. Edge Tracking by Hysteresis

- Importance of Edge Tracking

- Process of Connecting Weak Edges to Strong Edges

- Suppression of Unconnected Weak Edges

- Code Implementation