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Daniel Romaniuk
In this 1.5 hour long project-based course, you will apply computer vision techniques to process images, extract useful features and detect shapes using Hough transforms.
Read more
In this 1.5 hour long project-based course, you will apply computer vision techniques to process images, extract useful features and detect shapes using Hough transforms.
Read more
In this 1.5 hour long project-based course, you will apply computer vision techniques to process images, extract useful features and detect shapes using Hough transforms.
By the end of this project, you will have analyzed real-world images using industry standard tools, including Python and OpenCV.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/b16wrs/recognizing
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What's inside
Syllabus
Project Overview
In this 1.5 hour long project-based course, you will apply computer vision techniques to process images, extract useful features and detect shapes using Hough transforms. By the end of this project, you will have analyzed real-world images using industry standard tools, including Python and OpenCV.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers image processing and shape detection, which is standard in computer vision and data science
Uses Python and OpenCV, which are industry standard tools for computer vision
Builds a strong foundation for beginners in computer vision
Offers hands-on labs and interactive materials
Taught by Daniel Romaniuk, who is recognized for their work in computer vision
Suitable for learners based in the North America region
Save this course
Save Recognizing Shapes in Images with OpenCV to your list so you can find it easily later:
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Reviews summary
Beginner-friendly opencv intro
Learners say that this OpenCV course is a beginner-friendly introduction to line and circle detection. While students enjoyed the course, some found the Coursera's Rhyme environment to be problematic at times.
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Recognizing Shapes in Images with OpenCV with these
activities:
Read 'Computer Vision: Algorithms and Applications'
Show steps
Enhance your understanding of computer vision concepts by reviewing a comprehensive textbook on the subject.
View
Computer Vision
on Amazon
Show steps
-
Locate a copy of the book 'Computer Vision: Algorithms and Applications'.
-
Read and study the chapters relevant to the course.
-
Take notes and highlight important concepts.
Practice image processing techniques
Show steps
Practice applying the image processing techniques learned in this course.
Show steps
-
Find images to work with
-
Apply basic image processing techniques
-
Experiment with different parameters
-
Analyze the results and compare them
Follow tutorials on shape detection using Hough transforms
Show steps
Reinforce the concepts of shape detection using Hough transforms by following tutorials.
Show steps
-
Search for tutorials on Hough transforms
-
Watch and follow the tutorials
-
Apply the techniques learned in the tutorials
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice with Image Processing Tools
Show steps
Reinforce your understanding of image processing techniques by practicing with different image processing tools.
Browse courses on
Image Processing
Show steps
-
Install and set up image processing tools on your computer.
-
Load and display images using the image processing library.
-
Apply basic image processing operations, such as cropping, resizing, and filtering.
-
Explore advanced image processing techniques, such as morphological operations and feature extraction.
Create a presentation on the applications of image processing in a specific field
Show steps
Develop a deeper understanding of the practical applications of image processing.
Show steps
-
Choose a specific field of interest
-
Research the applications of image processing in the chosen field
-
Develop a presentation
-
Present it to an audience
Build an Image Processing Portfolio
Show steps
Showcase your skills and understanding by building a portfolio of image processing projects.
Show steps
-
Choose a variety of image processing projects that demonstrate different techniques and applications.
-
Develop and implement these projects using appropriate image processing tools.
-
Document your projects, including the problem statement, approach, and results.
-
Create a portfolio website or platform to showcase your projects.
Mentor junior students or beginners in image processing
Show steps
Solidify your understanding of image processing concepts by teaching others.
Show steps
-
Identify opportunities to mentor others
-
Share your knowledge and experience
-
Provide guidance and support
-
Evaluate the progress of your mentees
Read 'Computer Vision: Algorithms and Applications'
Show steps
Enhance your understanding of computer vision concepts by reviewing a comprehensive textbook on the subject.
View
Computer Vision
on Amazon
Show steps
Show steps
Show steps
- Locate a copy of the book 'Computer Vision: Algorithms and Applications'.
- Read and study the chapters relevant to the course.
- Take notes and highlight important concepts.
Practice image processing techniques
Show steps
Practice applying the image processing techniques learned in this course.
Show steps
Show steps
Show steps
- Find images to work with
- Apply basic image processing techniques
- Experiment with different parameters
- Analyze the results and compare them
Follow tutorials on shape detection using Hough transforms
Show steps
Reinforce the concepts of shape detection using Hough transforms by following tutorials.
Show steps
Show steps
Show steps
- Search for tutorials on Hough transforms
- Watch and follow the tutorials
- Apply the techniques learned in the tutorials
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice with Image Processing Tools
Show steps
Reinforce your understanding of image processing techniques by practicing with different image processing tools.
Browse courses on
Image Processing
Show steps
Show steps
Show steps
- Install and set up image processing tools on your computer.
- Load and display images using the image processing library.
- Apply basic image processing operations, such as cropping, resizing, and filtering.
- Explore advanced image processing techniques, such as morphological operations and feature extraction.
Create a presentation on the applications of image processing in a specific field
Show steps
Develop a deeper understanding of the practical applications of image processing.
Show steps
Show steps
Show steps
- Choose a specific field of interest
- Research the applications of image processing in the chosen field
- Develop a presentation
- Present it to an audience
Build an Image Processing Portfolio
Show steps
Showcase your skills and understanding by building a portfolio of image processing projects.
Show steps
Show steps
Show steps
- Choose a variety of image processing projects that demonstrate different techniques and applications.
- Develop and implement these projects using appropriate image processing tools.
- Document your projects, including the problem statement, approach, and results.
- Create a portfolio website or platform to showcase your projects.
Mentor junior students or beginners in image processing
Show steps
Solidify your understanding of image processing concepts by teaching others.
Show steps
Show steps
Show steps
- Identify opportunities to mentor others
- Share your knowledge and experience
- Provide guidance and support
- Evaluate the progress of your mentees
Career center
Learners who complete Recognizing Shapes in Images with OpenCV will develop knowledge and skills
that may be useful to these careers:
Computer Vision Researcher
Computer Vision Researcher
Computer Vision Researchers develop new algorithms and techniques for image processing and computer vision. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to conduct research and develop new solutions to complex problems in areas such as medical imaging, autonomous driving, and robotics.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers use their expertise in image processing, deep learning, and other artificial intelligence techniques to develop solutions to real-world problems. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop computer vision applications that can solve complex problems in areas such as medical imaging, autonomous driving, and robotics.
Image Processing Engineer
Image Processing Engineer
Image Processing Engineers use their expertise in image processing and computer vision techniques to develop solutions to real-world problems. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop image processing solutions that can solve complex problems in areas such as medical imaging, industrial inspection, and security.
Computer Vision Product Manager
Computer Vision Product Manager
Computer Vision Product Managers are responsible for developing and managing computer vision products. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop and manage computer vision products that solve complex problems in areas such as medical imaging, autonomous driving, and robotics.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve a wide range of business problems. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop machine learning models that can solve complex problems in areas such as object detection, facial recognition, and medical diagnosis.
Data Analyst
Data Analyst
Data Analysts use their expertise in statistics, data analysis, and machine learning to extract insights from data. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop data analysis solutions that can solve complex problems in areas such as medical imaging, fraud detection, and customer segmentation.
Data Scientist
Data Scientist
Data Scientists use their expertise in statistics, machine learning, and data analysis to extract insights from data. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop data science solutions that can solve complex problems in areas such as medical imaging, fraud detection, and customer segmentation.
Business Analyst
Business Analyst
Business Analysts use their expertise in business processes and data analysis to identify and solve business problems. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop business analysis solutions that can solve complex problems in areas such as process improvement, customer segmentation, and market research.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop software solutions that can solve complex problems in areas such as facial recognition, medical imaging, and robotics.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their expertise in mathematics, statistics, and computer science to solve complex problems in business and industry. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop operations research solutions that can solve complex problems in areas such as supply chain management, logistics, and manufacturing.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, develop, and maintain robots. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop robots that can solve complex problems in areas such as object manipulation, navigation, and human-robot interaction.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts use their expertise in testing and quality control to ensure that software products meet the highest standards. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop quality assurance solutions that can solve complex problems in areas such as software testing, product development, and manufacturing.
Technical Writer
Technical Writer
Technical Writers use their expertise in writing and communication to create technical documentation. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop technical documentation that can clearly and effectively communicate complex technical concepts.
User Experience Designer
User Experience Designer
User Experience Designers use their expertise in human-computer interaction and design to create user interfaces that are easy to use and enjoyable. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop user experience solutions that can solve complex problems in areas such as website design, mobile app development, and product development.
Product Designer
Product Designer
Product Designers use their expertise in design and engineering to create products that are both useful and desirable. This course, Recognizing Shapes in Images with OpenCV, provides a solid foundation in image processing and computer vision techniques that are essential for success in this field. By learning how to extract useful features from images and detect shapes using Hough transforms, you will gain the skills necessary to develop product design solutions that can solve complex problems in areas such as industrial design, consumer electronics, and medical devices.
For more career information including salaries, visit:
OpenCourser.com/course/b16wrs/recognizing
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Recognizing Shapes in Images with OpenCV.
Save
Comprehensive introduction to computer vision. It covers the fundamental algorithms and techniques used in computer vision, as well as a wide range of applications. It valuable resource for anyone who wants to learn more about computer vision.
Gentle introduction to computer vision using Python. It covers the basics of image processing, feature extraction, and object detection. It valuable resource for anyone who wants to learn more about computer vision without getting bogged down in the details.
Classic textbook on digital image processing. It covers a wide range of topics, from image enhancement to image segmentation. It valuable resource for anyone who wants to learn more about the fundamentals of digital image processing.
Modern classic in computer vision research and practice. It covers a wide range of topics, from the basics of image processing to the latest developments in computer vision. It valuable resource for anyone who wants to learn more about the state-of-the-art computer vision.
Save
Modern classic in computer vision research and practice. It covers a wide range of topics, from the basics of image processing to the latest developments in computer vision. It valuable resource for anyone who wants to learn more about the state-of-the-art in computer vision.
Provides a comprehensive overview of deep learning for computer vision applications. It covers a wide range of topics, from the basics of deep learning to the latest developments in computer vision.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/b16wrs/recognizing
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Effort
1.5 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Daniel Romaniuk
Language
English
Good to know
Covers image processing and shape detection, which is standard in computer vision and data science
Uses Python and OpenCV, which are industry standard tools for computer vision
Builds a strong foundation for beginners in computer vision
Offers hands-on labs and interactive materials
Taught by Daniel Romaniuk, who is recognized for their work in computer vision
Suitable for learners based in the North America region
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