Computer Vision Fundamentals with OpenCV and C#

Computer Vision Fundamentals with OpenCV and C#, available at $49.99, has an average rating of 4.35, with 56 lectures, based on 140 reviews, and has 694 subscribers.

You will learn about They will be able to develop applications such as barcode reading , text segmentation, object tracking, OCR techniques, document control This course is ideal for individuals who are Software developers wanting to develop computer vision applications It is particularly useful for Software developers wanting to develop computer vision applications.

Enroll now: Computer Vision Fundamentals with OpenCV and C#

Summary

Title: Computer Vision Fundamentals with OpenCV and C#

Price: $49.99

Average Rating: 4.35

Number of Lectures: 56

Number of Published Lectures: 56

Number of Curriculum Items: 56

Number of Published Curriculum Objects: 56

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

They will be able to develop applications such as barcode reading , text segmentation, object tracking, OCR techniques, document control

Who Should Attend

Software developers wanting to develop computer vision applications

Target Audiences

Software developers wanting to develop computer vision applications

Hi,

Please meet the first video course ever in Computer Vision Fundamentals covered using C# programming language and OpenCV wrapper OpenCVSharp .

This course will teach you how to enter the wonderful world of computer vision using C# programming language and one of the most widely used open source Computer Vision Library, namely the OpenCV. You will learn in particular, how to utilize a popular C# wrapper of OpenCV, which is the OpenCVSharp.

Once you grasp the fundamentals of Computer Vision following this course, you will then be able to follow the more advanced future courses in Computer Vision and Deep Learning field that I will be recording.

In this course, you will learn the fundamentals of image processing which will open the way for you to tackle problems such as Barcode Recognition, Webcam programming, Text Segmentation and OCR techniques to read text from scanned documents.

You will learn in particular:

How to read images from disk and display them and save images to disk

Learn about Mat type object of OpenCV

Image pixel manipulations

Drawing on images

Locating a Region of Interest area and Cropping

Gray Scale Image conversion

Image Thresholding Techniques

Image Binarization

Image Bitwise operations

Image Filters- Image Convolution

Gaussian Blur

Median Blur

HighPass filters

Sobel, Scharr Edge Detection methods

Canny Edge Detection

OpenCV Trackbar Programming for changing input parameters by a user control

Shape Contour detection

Contour Repair

Image Resizing

Image Rotation

Image Flipping

Morphological Operations (Erosion, Dilation, Opening, Closing, TopHat, BlackHat)

Contour Smoothing

Convex Hull, Non-Convex defects

Shape Matching

Image Masking

Image Histograms, Histogram Plotting

Real-life Applications (step by step explanations and coding ) : Barcode detection and decoding from a food package, Object Tracking via its color using a webcam, text OCR with tesseract plus OpenCV)

Plus the “Assignments” designed to help you get advanced skills in computer vision ( Hand Gesture Detection, Color image channel histograms, Coin counting, Textile Defect Detection)

Soon you will find the source code updated to the latest version of OpenCVSharp, which is OpenCVSharp4(8/2/2024)

I have already updated and then uploaded the source code of the Barcode reading section(8/2/2024)

With my best regards,

Frank Ozz

Course Curriculum

Chapter 1: Introduction

Lecture 1: Update of the source code

Lecture 2: Introduction

Chapter 2: CHAPTER 1- INTRODUCTION TO WRAPPERS AND TABLE OF CONTENTS OF THE COURSE

Lecture 1: Section 1.1- OpenCV Wrappers for C#

Lecture 2: Section 1.1 Table of Contents

Chapter 3: CHAPTER 2-IMAGE LOADING, DISPLAYING AND SAVING

Lecture 1: Section 2.1 Image Loading, Displaying and Saving

Chapter 4: CHAPTER 3-IMAGE BASICS

Lecture 1: Section 3.1- Image Basics, Image Elements

Chapter 5: CHAPTER 4-MAT CLASS OF OPENCV

Lecture 1: Section 4-1 Mat object introduction

Lecture 2: Section 4.2- Mat object creation

Lecture 3: Section 4.3 Copying and Cloning Mat objects

Lecture 4: Section 4.4 Splitting Mat type image to its channels, roi creation and cropping

Lecture 5: Section 4.5 Mat Object Image Manipulation

Lecture 6: Section 4.6 Mat Object Image Manipulation Second Part

Lecture 7: Section 4.7 Drawing Shapes on Images

Chapter 6: CHAPTER 5

Lecture 1: Section 5.1 Intro

Lecture 2: Section 5.2 Image Shifting

Lecture 3: Section 5.3 Image Rotation

Lecture 4: Section 5.4 Image Resizing

Lecture 5: Section 5.5 Image Flipping

Lecture 6: Section 5.6 Bitwise Operations On Images

Chapter 7: CHAPTER 6- THRESHOLDING

Lecture 1: Section 6.1 Intro

Lecture 2: Chapter 6.2 Part 2

Lecture 3: Section 6.3 Otsu ıntro

Lecture 4: Section 6.3.1 Otsu Coding

Chapter 8: CHAPTER 7- HISTOGRAM

Lecture 1: Section 7.1 Introduction to Histogram concept and the OpenCv CalcHist method

Lecture 2: Section 7.2 Plotting Histogram of an Image

Chapter 9: CHAPTER 8-FILTERING IMAGES

Lecture 1: Section 8.1 Filters and Convolution Intro

Lecture 2: Section 8.2 Loas Pass Filters

Lecture 3: Chapter 8.2 Filter Demo 1

Lecture 4: Chapter 8.2 Filter Demo 2

Lecture 5: Chapter 8.3 Sobel Filter Intro

Lecture 6: Chapter 8.3 Sobel Filter 1

Lecture 7: Chapter 8.3 Sobel Filter 2

Chapter 10: Section 10- Canny Edge Detection

Lecture 1: Chapter 9.1 Canny Edge Detection Method Intro

Lecture 2: Chapter 9.2 Canny Edge Detection Implementation

Lecture 3: Chapter 9.3 Implementing OpenCV Trackbar for changing Canny method parameters

Lecture 4: Chapter 9.4 Canny Algorithm- What goes on behind the scenes?

Chapter 11: Section 11- Contour Detection and Contour Analysis

Lecture 1: Chapter 10 Contour and Shape Intro

Lecture 2: Chapter 10 Part 1 Contour Detection

Lecture 3: Chapter 10 Part 2.1 Shape Matching Intro

Lecture 4: Chapter 10 Part 2.1 Shape Matching Demo

Lecture 5: Chapter 10 Part 2.2 Case of Missing Pizza Slice Intro

Lecture 6: Chapter 10 Part 2.2 Case of Missing Pizza Slice Demo

Chapter 12: Section 12- Morphological Operations

Lecture 1: Chapter 11 Part 1 Morphological Ops Intro

Lecture 2: Chapter 11 Erosion and Dilation Part 1

Lecture 3: Chapter 11 Erosion and Dilation Part 2

Lecture 4: Assignment- Develop a Hand Gesture Decoding software using Webcam image stream

Chapter 13: Appendix A- Object Tracking via webcam and object color

Lecture 1: Object Tracking Part 1

Lecture 2: Object Tracking Part 2

Lecture 3: Object Tracking Part 3

Chapter 14: Appendix B- Barcode Detection and Decoding

Lecture 1: Part 1- Problem Definition

Lecture 2: Part 2

Lecture 3: Part 3

Lecture 4: Part 4

Lecture 5: Part 5

Lecture 6: Part 6

Lecture 7: Exercise- Extending the barcode reader software with webcam

Instructors

F. Frank Ozz
Software Architect, Author

Rating Distribution

1 stars: 2 votes
2 stars: 5 votes
3 stars: 26 votes
4 stars: 44 votes
5 stars: 63 votes

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