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⇱ Introduction to Computer Vision | Coursera


Introduction to Computer Vision

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Introduction to Computer Vision

This course is part of multiple programs.

14,087 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.6

59 reviews

Intermediate level

Recommended experience

8 hours to complete

Gain insight into a topic and learn the fundamentals.
4.6

59 reviews

Intermediate level

Recommended experience

8 hours to complete

What you'll learn

  • Use common algorithms for feature detection, extraction, & matching

  • Perform image registration by identifying control points & estimating geometric transformations

  • Complete a final project where you stitch together images from NASA’s Mars Curiosity Rover

  • Combine images with image stitching to create panorama images

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

6 assignments

Taught in English
Flexible schedule
Learn at your own pace

Build your subject-matter expertise

This course is available as part of
When you enroll in this course, you'll also be asked to select a specific program.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

In the first course of the Computer Vision for Engineering and Science specialization, you’ll be introduced to computer vision. You'll learn and use the most common algorithms for feature detection, extraction, and matching to align satellite images and stitch images together to create a single image of a larger scene.

Features are used in applications like motion estimation, object tracking, and machine learning. You’ll use features to estimate geometric transformations between images and perform image registration. Registration is important whenever you need to compare images of the same scene taken at different times or combine images acquired from different scientific instruments, as is common with hyperspectral and medical images. You will use MATLAB throughout this course. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your computer vision tasks. You will be provided free access to MATLAB for the course duration to complete your work. To be successful in this course, it will help to have some prior image processing experience. If you are new to image data, it’s recommended to first complete the Image Processing for Engineering and Science specialization.

What's included

2 videos4 readings1 assignment1 discussion prompt

2 videosβ€’Total 6 minutes
  • Computer Vision for Engineering and Scienceβ€’3 minutes
  • Introduction: What Are Features?β€’3 minutes
4 readingsβ€’Total 40 minutes
  • Prerequisite Knowledge β€’5 minutes
  • Meet Your Instructorsβ€’5 minutes
  • Download and Install MATLABβ€’15 minutes
  • Course Filesβ€’15 minutes
1 assignmentβ€’Total 15 minutes
  • Graded Quiz: Introduction to Featuresβ€’15 minutes
1 discussion promptβ€’Total 10 minutes
  • Choosing a Feature Typeβ€’10 minutes

What's included

3 videos3 readings1 assignment1 discussion prompt

3 videosβ€’Total 13 minutes
  • Detecting Featuresβ€’5 minutes
  • Extracting Featuresβ€’5 minutes
  • Matching Featuresβ€’4 minutes
3 readingsβ€’Total 85 minutes
  • Refining Feature Detectionβ€’45 minutes
  • Feature Detection and Extraction Referenceβ€’10 minutes
  • Matching Featuresβ€’30 minutes
1 assignmentβ€’Total 45 minutes
  • Graded Quiz: Detecting, Extracting, and Matching Featuresβ€’45 minutes
1 discussion promptβ€’Total 10 minutes
  • Feature Detection on Your Own Imagesβ€’10 minutes

What's included

3 videos1 reading2 assignments

3 videosβ€’Total 18 minutes
  • Estimating and Applying Geometric Transformationsβ€’6 minutes
  • Feature-Based Image Registrationβ€’8 minutes
  • Visually Selecting Control Pointsβ€’4 minutes
1 readingβ€’Total 20 minutes
  • Practice With Geometric Transformationsβ€’20 minutes
2 assignmentsβ€’Total 75 minutes
  • Graded Quiz: Image Registrationβ€’60 minutes
  • Concept Check: Geometric Transformationsβ€’15 minutes

What's included

2 videos4 readings2 assignments1 app item1 discussion prompt1 plugin

2 videosβ€’Total 9 minutes
  • Stitching Images Togetherβ€’7 minutes
  • Summary of Introduction to Computer Visionβ€’2 minutes
4 readingsβ€’Total 67 minutes
  • Introduction to Image Stitchingβ€’30 minutes
  • Stitching Images Exampleβ€’20 minutes
  • Mars Rover: Your Final Projectβ€’15 minutes
  • What's Next?β€’2 minutes
2 assignmentsβ€’Total 40 minutes
  • Project: Check the Panorama Imageβ€’30 minutes
  • Concept Check: Image Stitchingβ€’10 minutes
1 app itemβ€’Total 30 minutes
  • Project: Check Your Registration Functionβ€’30 minutes
1 discussion promptβ€’Total 10 minutes
  • Project: Third Mars Rover Imageβ€’10 minutes
1 pluginβ€’Total 5 minutes
  • Share Your Feedbackβ€’5 minutes

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Instructors

Instructor ratings
4.6 (14 ratings)
MathWorks
9 Coursesβ€’48,845 learners

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Learner reviews

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JS
Β·

Reviewed on Sep 19, 2024

Excellent course, is very in depth and requires some familiarity with Matlab and image processing

Frequently asked questions

Yes. A free license is available to learners enrolled in the course. You must have a computer capable of running MATLAB. You can view the system requirements here.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Financial aid available,