Introduction to Computer Vision

Introduction to Computer Vision, available at $54.99, has an average rating of 4.5, with 52 lectures, based on 1 reviews, and has 18 subscribers.

You will learn about Become an advanced, confident, and modern Computer Vision expert from scratch How to think and work like a developer: problem-solving, researching, workflows Digital image processing: gray level transformations, geometric transformations, convolution, image enhancement and smoothing, morphological filters, etc. Get fast and friendly support in the Q&A area This course is ideal for individuals who are Take this course if you want to start your journey in Computer Vision or Take this course if you have been trying to learn Computer Vision but: 1) still dont really understand Computer Vision, or 2) still dont feel confident to work real projects It is particularly useful for Take this course if you want to start your journey in Computer Vision or Take this course if you have been trying to learn Computer Vision but: 1) still dont really understand Computer Vision, or 2) still dont feel confident to work real projects.

Enroll now: Introduction to Computer Vision

Summary

Title: Introduction to Computer Vision

Price: $54.99

Average Rating: 4.5

Number of Lectures: 52

Number of Published Lectures: 51

Number of Curriculum Items: 53

Number of Published Curriculum Objects: 52

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

Become an advanced, confident, and modern Computer Vision expert from scratch

How to think and work like a developer: problem-solving, researching, workflows

Digital image processing: gray level transformations, geometric transformations, convolution, image enhancement and smoothing, morphological filters, etc.

Get fast and friendly support in the Q&A area

Who Should Attend

Take this course if you want to start your journey in Computer Vision

Take this course if you have been trying to learn Computer Vision but: 1) still dont really understand Computer Vision, or 2) still dont feel confident to work real projects

Target Audiences

Take this course if you want to start your journey in Computer Vision

Take this course if you have been trying to learn Computer Vision but: 1) still dont really understand Computer Vision, or 2) still dont feel confident to work real projects

Do you want to start your journey in Computer Vision?

Or is it that Computer Vision interests you?

If you need a quick brush-up, or learning Computer Vision for the first time, you’ve come to the right place!

Let’s get started learning one of the most interesting computer science topics out there right now. There’s no need to fret if you haven’t coded before. This courses starts from scratch.

Computer Vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering and computer science, it seeks to understand and automate tasks that the human visual system can do. This course will be a quick way to introduce to the Computer Vision world. You’ll be a whiz in no time.

We’ll begin with the basics of Computer Vision, learning about the digital image, discretization, domains and getting to know the image quantification. We’ll soon move on to the basics of image information retrieval in Computer Vision.

Now, after completing this Introduction Course you can finish your training with The Complete Computer Vision Course available in my udemy profile with more than 12 hours duration.

I hope you’re excited to dive into the World of Computer Vision with this course. Well, what are you waiting for? Let’s get started!

Course Curriculum

Chapter 1: Course Overview

Lecture 1: Course Introduction

Lecture 2: Learning MATLAB

Chapter 2: The Digital Image

Lecture 1: Basic Concepts

Lecture 2: Discretization of the Image

Lecture 3: Working with Images

Lecture 4: Domain Evaluation

Lecture 5: How to Save an Image

Lecture 6: Mesh Function

Chapter 3: Image Quantification

Lecture 1: Introduction to Colour Quantification

Lecture 2: RGB and HSI Models

Chapter 4: Image Preprocessing

Lecture 1: Introduction to Image Preprocessing

Lecture 2: Image Information Retrieval

Lecture 3: Gray Level Histogram

Lecture 4: Histogram Equalization

Lecture 5: Affine Transformation

Lecture 6: Arithmetic Operations

Lecture 7: Quality Control Project – Statement

Lecture 8: Quality Control Project – Solution – Part 1

Lecture 9: Quality Control Project – Solution – Part 2

Lecture 10: Introduction to Convolution

Lecture 11: Working with Convolution

Lecture 12: Image Noise and Smoothing Filters

Lecture 13: Contour Detection

Chapter 5: Morphological Image Processing

Lecture 1: Introduction to Morphological Image Processing

Lecture 2: Dilations

Lecture 3: Erosions

Lecture 4: Morphological Gradients

Lecture 5: Distance Transform

Lecture 6: Conditional Dilation and Reconstruction

Lecture 7: Challenge 1 – Wrench Reconstruction

Lecture 8: Challenge 2 – Greek Symbols

Lecture 9: Challenge 3 – Closed Holes

Lecture 10: Opening and Closing

Lecture 11: Gear Detection

Lecture 12: Skeletons

Lecture 13: Morphology for Multilevel Images

Chapter 6: MATLAB Fundamentals – Commands

Lecture 1: Introduction to Commands

Lecture 2: Output in MATLAB

Chapter 7: MATLAB Fundamentals – Variables

Lecture 1: Introduction to Variables

Lecture 2: Storage and Data Loading

Lecture 3: Using Constants and built-in Functions

Chapter 8: MATLAB Fundamentals – Desktop and Editor

Lecture 1: MATLAB Environment Overview

Lecture 2: MATLAB Editor

Chapter 9: MATLAB Fundamentals – Arrays

Lecture 1: Introduction to Arrays

Lecture 2: Arrays and Spacing

Lecture 3: Array Creation Functions

Lecture 4: Indexing

Lecture 5: Extracting Multiple Elements

Chapter 10: MATLAB Fundamentals – Plots

Lecture 1: Plotting Arrays

Lecture 2: Plots Annotation

Chapter 11: MATLAB Fundamentals – Electricity Usage Project

Lecture 1: Electricity Usage

Instructors

Lucas Bazilio
Engineer and Mathematician

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