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Andrey Savchenko, Alexander Smorkalov, Alexander Demidovskij, and Anastasiia Sokolova
The course is devoted to the usage of computer vision libraries like OpenCV in 2d image processing. The course includes sections of image filtering and thresholding, edge/corner/interest point detection, local and global descriptors, video tracking. Aim of the course: • Learning the main algorithms of traditional image processing • Thorough understanding of benefits and limitations of traditional image processing Practical Learning Outcomes expected: • Mastering programming skills of image processing with computer vision libraries This Course is part of HSE University Master of Computer Vision degree program. Learn more about...
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The course is devoted to the usage of computer vision libraries like OpenCV in 2d image processing. The course includes sections of image filtering and thresholding, edge/corner/interest point detection, local and global descriptors, video tracking. Aim of the course: • Learning the main algorithms of traditional image processing • Thorough understanding of benefits and limitations of traditional image processing Practical Learning Outcomes expected: • Mastering programming skills of image processing with computer vision libraries This Course is part of HSE University Master of Computer Vision degree program. Learn more about the admission into the program and how your Coursera work can be leveraged if accepted into the program here https://inlnk.ru/r381p.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by recognized computer vision experts from HSE University
Develops core computer vision and image analysis skills
Layes a foundation for advanced study in image processing or computer vision
May require additional hardware or software not found in a typical household
Uses OpenCV, an older but still popular computer vision library
May be less relevant for those already familiar with image processing techniques

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Reviews summary

Difficult to follow accent

This course is not recommended due to its difficult to follow content. One reviewer mentions that it is hard to follow along with the videos due to the lecturer's accent.
Lecturer's accent makes it hard to follow.
"...difficult to follow fluently the videos with lecturers' accent."

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 2D image processing with these activities:
Review OpenCV functions
Familiarizes students with the OpenCV library and its functions to aid in understanding image processing algorithms.
Browse courses on OpenCV
Show steps
  • Explore OpenCV documentation
  • Practice using OpenCV functions in a sandbox environment
Follow OpenCV tutorials
Provides hands-on experience and reinforces understanding of OpenCV concepts through structured tutorials.
Browse courses on OpenCV
Show steps
  • Identify relevant OpenCV tutorials for specific image processing tasks
  • Follow tutorials step-by-step and implement OpenCV functions
Join OpenCV discussion forums
Fosters collaboration and knowledge exchange by connecting students with other learners and experts in the field.
Browse courses on OpenCV
Show steps
  • Find relevant OpenCV discussion forums
  • Participate in discussions and ask questions
  • Share knowledge and help others understand image processing concepts
Five other activities
Expand to see all activities and additional details
Show all eight activities
Seek guidance from experienced image processing professionals
Connects students with experts who can provide personalized guidance and support, accelerating their learning journey.
Browse courses on OpenCV
Show steps
  • Identify image processing professionals in academia or industry
  • Reach out and request mentorship or guidance
  • Meet regularly to discuss progress and receive feedback
  • Benefit from the mentor's experience and insights
Develop image processing demos
Encourages students to apply their understanding of image processing algorithms by creating practical demonstrations.
Browse courses on Image Processing
Show steps
  • Choose an image processing task to demonstrate
  • Design and implement an algorithm in OpenCV
  • Create a visual representation or user interface for the demo
Create an OpenCV resource collection
Encourages students to organize and curate relevant resources, aiding in their mastery of the subject matter.
Browse courses on OpenCV
Show steps
  • Gather tutorials, documentation, and code samples related to OpenCV
  • Categorize and organize the resources
  • Share the collection with others
Volunteer in an image processing lab
Provides hands-on experience in a real-world setting, exposing students to practical applications of image processing.
Browse courses on OpenCV
Show steps
  • Find image processing labs or research groups accepting volunteers
  • Inquire about volunteer opportunities and requirements
  • Assist researchers or engineers with image processing tasks
Participate in OpenCV hackathons
Challenges students to apply their skills and knowledge in a competitive setting, fostering innovation and problem-solving abilities.
Browse courses on OpenCV
Show steps
  • Find OpenCV-related hackathons
  • Form a team or participate individually
  • Develop an image processing solution within a time constraint

Career center

Learners who complete 2D image processing will develop knowledge and skills that may be useful to these careers:
Computer Vision Scientist
Computer Vision Scientists are developing, researching, and applying computer vision techniques to real-world problems. This includes developing algorithms used for image and video analysis, while building solutions to problems in areas such as medical imaging, remote sensing, and industrial inspection. These applications may also be used in self-driving cars and facial recognition systems.
Image Processing Engineer
Image Processing Engineers develop and implement algorithms to process and analyze images. This can involve working with a variety of image formats, as well as developing techniques to improve image quality and extract information from images. Gaining the skills needed to filter and threshold images by completing this course will be useful to careers in this field.
Robotics Engineer
Robotics Engineers are responsible for designing, building, and testing robots. They are also responsible for developing code to control these robots. By building a foundation in image processing with this course, you'll gain skills in filtering images to help these robots sense their environments and interact with them effectively.
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models. These models can be used for a variety of tasks, such as image recognition, natural language processing, and predictive analytics. Building a foundation in image processing with this course will help with your ability to develop and fine-tune the models used in computer vision.
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data. They are also responsible for developing and deploying machine learning models. Gaining the skills needed to filter images by completing this course may be useful to careers in this field.
Software Engineer
Software Engineers are responsible for designing, developing, and testing software applications. They are also responsible for maintaining and updating these applications. Gaining the skills needed to filter and threshold images by completing this course may be useful to careers in this field.
Computer Programmer
Computer Programmers are responsible for writing and maintaining computer programs. They are also responsible for testing and debugging these programs. Gaining the skills needed to filter and threshold images by completing this course may be useful to careers in this field.
Web Developer
Web Developers are responsible for designing and developing websites. They are also responsible for maintaining and updating these websites. Gaining the skills needed to filter and threshold images by completing this course may be useful to careers in this field.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. They are also responsible for ensuring that these databases are secure and reliable. Gaining the skills needed to filter and threshold images by completing this course may be useful to careers in this field.
Information Security Analyst
Information Security Analysts are responsible for protecting computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. Gaining the skills needed to filter and threshold images by completing this course may be useful to careers in this field.
System Analyst
System Analysts are responsible for analyzing and designing computer systems. They are also responsible for implementing and maintaining these systems.
Network Administrator
Network Administrators are responsible for managing and maintaining computer networks. They are also responsible for ensuring that these networks are secure and reliable.
Computer Support Specialist
Computer Support Specialists are responsible for providing technical support to computer users. They are also responsible for troubleshooting and resolving computer problems.
Help Desk Technician
Help Desk Technicians are responsible for providing technical support to computer users. They are also responsible for troubleshooting and resolving computer problems.
Data Entry Clerk
Data Entry Clerks are responsible for entering data into computer systems. They are also responsible for verifying and correcting data.

Reading list

We've selected eight 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 2D image processing.
Provides a comprehensive overview of computer vision algorithms and techniques, covering topics such as image formation, feature detection, object recognition, and motion tracking. It valuable resource for anyone interested in learning more about the fundamentals of computer vision.
This textbook provides a modern and comprehensive introduction to computer vision, covering topics such as image formation, feature detection, object recognition, and motion tracking. It valuable resource for anyone interested in learning more about the latest advances in computer vision.
This textbook provides a comprehensive introduction to digital image processing, covering topics such as image enhancement, image analysis, and image compression. It valuable resource for anyone interested in learning the basics of digital image processing.
Provides a practical introduction to computer vision using the OpenCV library. It covers topics such as image processing, feature detection, object recognition, and motion tracking. It valuable resource for anyone interested in learning how to use OpenCV for computer vision applications.
This classic textbook provides a comprehensive introduction to digital image processing, covering topics such as image enhancement, image analysis, and image compression. It valuable resource for anyone interested in learning the basics of digital image processing.
Provides an introduction to deep learning for computer vision, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone interested in learning how to use deep learning for computer vision applications.
This cookbook provides a collection of recipes for solving common computer vision problems using the OpenCV library. It covers topics such as image processing, feature detection, object recognition, and motion tracking. It valuable resource for anyone interested in learning how to use OpenCV for computer vision applications.
This cookbook provides a collection of recipes for solving common computer vision problems using the OpenCV library. It covers topics such as image processing, feature detection, object recognition, and motion tracking. It valuable resource for anyone interested in learning how to use OpenCV for computer vision applications.

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