About this Course
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Flexible deadlines

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Intermediate Level

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Approx. 12 hours to complete

Suggested: 4 weeks of study, 4-5 hours per week...

English

Subtitles: English

What you will learn

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    Design and build image processing applications

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    Examine the different types of image transformations

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    Analyze images in frequency domain

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    Understand image features and segmentation

Skills you will gain

Image ProcessingImage SegmentationComputer ProgrammingMatlab

Course 2 of 4 in the

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations

Approx. 12 hours to complete

Suggested: 4 weeks of study, 4-5 hours per week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
7 hours to complete

Image Processing Fundamentals

In this module, we will discuss the basics and applications of digital image processing, including intensity transformations and color image processing.

...
4 videos (Total 20 min), 2 readings, 8 quizzes
4 videos
Image Processing Basics4m
Intensity Transformations4m
Color Image Processing3m
2 readings
Resources (Optional): Image Processing Fundamentals30m
REQUIRED- MATLAB Resources10m
2 practice exercises
Image Processing Basics6m
Intensity Transformations5m
Week
2
4 hours to complete

Image Filters

In this module, we will discuss image filtering as well as some advanced image processing methods.

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5 videos (Total 26 min), 1 reading, 7 quizzes
5 videos
Filtering in Frequency Domain4m
Multi-Resolution Processing & Compression6m
Morphological Image Processing3m
Advanced Image Processing3m
1 reading
Resources (Optional): Image Filters30m
5 practice exercises
Spatial Image Filtering20m
Filtering in Frequency Domain6m
Multi-Resolution Processing & Compression5m
Morphological Image Processing15m
Advanced Image Processing2m
Week
3
2 hours to complete

Image Features & Matching

In this module, we will discuss image features, feature matching, texture matching, and how to create a panorama.

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5 videos (Total 21 min), 1 reading, 5 quizzes
5 videos
Scale Invariant Image Features5m
Feature Matching1m
Creating a Panorama4m
Texture Matching2m
1 reading
Resources (Optional): Image Features and Matching30m
4 practice exercises
Image Features
Scale Invariant Image Features6m
Feature Matching2m
Texture Matching2m
Week
4
3 hours to complete

Image Segmentation

This module describes what image segmentation is and provides information on the different techniques used to perform image segmentation.

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6 videos (Total 15 min), 2 readings, 4 quizzes
6 videos
State-of-the-Art Image Segmentation2m
Early Segmentation Techniques3m
Segmentation & Clustering3m
Probabilistic Segmentation58s
Graph Cut Segmentation57s
2 readings
Resources (Optional): Image Segmentation30m
Image Processing, Features & Segmentation - Key Takeaways15m
2 practice exercises
Segmentation & Clustering6m
Probabilistic Segmentation2m

Instructors

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Radhakrishna Dasari

Instructor
Department of Computer Science
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Junsong Yuan

Associate Professor and Director of Visual Computing Lab
Computer Science and Engineering

About University at Buffalo

The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs....

About The State University of New York

The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe....

About the Computer Vision Specialization

This specialization provides a foundation in the rapidly expanding research field of computer vision, laying the groundwork necessary for designing sophisticated vision applications. Learners explore the integral elements that enable vision applications, ranging from editing images to reading traffic signs in self-driving cars to factory robots navigating around human co-workers. Content includes image processing and state-of-the-art vision techniques, augmented by insights from top leaders in the computer vision field. Learners gain hands-on experience writing computer vision programs through online labs using MATLAB and supporting toolboxes. The specialization is taught in MATLAB* using computer vision and supporting toolboxes. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables). To learn more, check out a video overview at https://youtu.be/OfxVUSCPXd0. * A free license to install MATLAB for the duration of the course is available from MathWorks....
Computer Vision

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, 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. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.