Computer Vision & Image Processing Course | IIT Guwahati | Prof. M.K. Bhuyan
Course Details
| Exam Registration | 2383 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Electrical, Electronics and Communications Engineering, Computer Science and Engineering |
| Credit Points | 3 |
| Level | Undergraduate/Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 26 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Master the Fundamentals of Computer Vision and Image Processing
In today's technology-driven world, the ability to interpret and understand visual data is paramount. From autonomous vehicles and medical diagnostics to facial recognition and augmented reality, Computer Vision (CV) and Image Processing are at the heart of modern innovation. If you're an undergraduate, postgraduate student, or researcher looking to build a strong foundation in this exciting field, a structured, expert-led course is invaluable.
This article details a comprehensive 12-week course designed and taught by a leading authority in the field, offering a deep dive into the core principles and cutting-edge applications of computer vision.
Meet Your Instructor: A Renowned Expert in the Field
The course is led by Prof. M. K. Bhuyan of IIT Guwahati, a distinguished figure with nearly three decades of experience. His impressive credentials include:
- Ph.D. from IIT Guwahati and postdoctoral research at the University of Queensland, Australia.
- Recipient of prestigious awards like the National Award for Best Applied Research (presented by the President of India) and the Fulbright-Nehru Fellowship.
- Senior IEEE Member and current Professor at IIT Guwahati, also serving as Dean of Infrastructure.
- Author of the textbook "Computer Vision and Image Processing: Fundamentals and Applications" (CRC Press, 2019).
- Extensive research interests spanning Machine Learning, AI, Video Processing, Human-Computer Interaction, and Biomedical Signal Processing.
Learning from an instructor of this caliber ensures you gain insights from both deep academic knowledge and practical industry experience.
Course Overview: What You Will Learn
This course is meticulously structured to take you from the basic building blocks to advanced applications of computer vision. It is ideal for students interested in academic research or a career in industries developing vision-based solutions.
Intended Audience: UG, PG, and Ph.D. students.
Prerequisites: Basic knowledge of coordinate geometry, matrix/linear algebra, and random processes.
Level: Undergraduate/Postgraduate
Duration: 12 Weeks
Detailed 12-Week Course Curriculum
The course layout is designed for progressive learning, ensuring a solid grasp of each concept before moving to the next.
| Week | Topics Covered |
|---|---|
| Week 1-3 | Fundamentals of Image Formation: Introduction to CV goals, radiometry, geometric transformations, camera models, calibration, and stereo vision. |
| Week 4-6 | Core Image Processing: Image transforms (like Fourier), image enhancement, filtering, color processing, and segmentation. |
| Week 7-9 | Feature & Descriptor Extraction: Texture, color, edges, shape representation, and key detectors like SIFT, SURF, and HOG. |
| Week 10 | Machine Learning Foundations: Linear regression, statistical decision theory, clustering, dimensionality reduction, and Linear Discriminant Analysis. |
| Week 11-12 | Advanced Applications: Neural Networks (ANN, CNN, Autoencoders), gesture recognition, motion estimation, object tracking, and practical programming assignments. |
Key Takeaways and Learning Outcomes
By completing this course, you will:
- Understand the fundamental concepts and mathematical models behind image formation and processing.
- Gain proficiency in essential techniques for feature extraction, pattern recognition, and image analysis.
- Build a foundation in machine learning as applied to computer vision tasks.
- Be equipped to understand current research literature and tackle real-world problems in fields like healthcare, automation, and robotics.
- Develop practical skills through programming assignments focused on implementation.
Essential Reference Books
To supplement the course material, the following textbooks are highly recommended:
- Forsyth & Ponce: "Computer Vision: A Modern Approach"
- M.K. Bhuyan: "Computer Vision and Image Processing: Fundamentals and Applications"
- Richard Szeliski: "Computer Vision: Algorithms & Applications"
Who Should Enroll?
This course is perfectly suited for students and professionals in Electrical Engineering, Electronics & Communication, Computer Science, and related disciplines who aspire to specialize in computer vision. The curriculum supports both academic research pathways and roles in software industries that develop cutting-edge computer vision applications.
Embark on this 12-week journey to transform your understanding of how machines see and interpret the world, guided by one of India's leading experts in the field.
Enroll Now →