B.E. (Automation and Robotics) Machine Vision System Syllabus - Mumbai University 2026
The University has moved this degree onto NEP 2020 one year at a time. The first and second years are NEP 2020 syllabi; the third and fourth years are still examined on the REV-2019 'C' Scheme, which is what the University sets for them this year.
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Syllabus for Machine Vision System
Computer Graphics, Sensors Technology, Robot Programming, Artificial Intelligence for Robotics
Module 1
- Introduction to Machine Vision : Computer and Human Vision Systems, the Human Eye, Computer versus Human Vision Systems, Evolution of Computer Vision, Computer/Machine Vision and Image Processing, Applications of Computer Vision.
Module 2: Digital Image Fundamentals : Digital Image Fundamentals Elements of visual perception, Monochrome and Colour Images, Image Brightness and Contrast., 2D, 3D, and 4D Images, Digital Image Representation , Digital Image File Formats, Fundamental Image Operations, Points, Edges, and Vertices, Point Operations, Thresholding, Brightness, Geometric Transformations, Spatial Transformation,
- Affine Transformation, Image Interpolation, Nearest-Neighbour Interpolation, Bilinear Interpolation, Bi-cubic Interpolation, Fundamental Steps in Digital Image Processing.
Module 3: Machine Vision and System Components : Machine Vision System, Machine Vision Camera: CCD and CMOS Image Sensors, TDI Sensor, Camera Type - Area Scan Cameras, Line Scan Cameras, Smart Cameras, Camera Lens Resolution, Contrast and Sharpness, Lenses and their parameters: Types of Lenses, Lens Mounts, Lens Selection Examples-Field of View Much larger than Camera sensor size or
- Smaller or close to Camera Sensor size, Machine Vision Lighting: Lighting: Light Sources in Machine Vision, Illumination Techniques-Backlighting, Front Lighting, Diffused Lighting, Oblique Lighting, Dark Field Lighting, Infrared and Ultraviolet Light, Filters, Machine Vision Software, Machine Vision Automation, Integration of Machine vision Components. to number of respective lecture hours mentioned in the curriculum.
Reference Books
- 1 Chiranji Lal Chowdhary, Mamoun Alazab, Ankit Chaudhary, Saqib Hakak and Thippa Reddy Gadekallu, Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches, Fundamentals, technologies and applications, IET COMPUTING SERIES 42
- 2 Joe Minichino Joseph Howse, learning Open CV
- 3 Computer Vision with Python, Second Edition, Packet Publishing Ltd.
- 4 Alexander Hornberg, ― Handbook of Machine and Computer Vision the Guide for Developers and Users.
- 1 Sheila Anand and L. Priya, ―A Guide for Machine Vision in Quality Control, Taylor & Francis Inc., Imprint CRC Press Inc., Dec 2019.
- 2 Rafael C. Gonzalez and Richard E. Woods, ―Digital Image Processing‖, Pearson
- 3 Carsten Stegar, Markus Ulrich, and Christian Wiedemann , ―Machine Vision Algorithms and U University of Mumbai Applications, Second completely Revised and Enlarged Edition.
- 4 Milan Sonka, Vaclav Hlavac, Roger Boyle, ―Image Processing Analysis and Machine Vision, Second Edition, Cengage Learning.
- 1 https://nptel.ac.in/courses/108103174
- 2 https://www.coursera.org/learn/introduction-computer-vision-watson-opencv
- 3 https://www.udacity.com/course/introduction-to-computer-vision--ud810
- 4 https://onlinecourses.nptel.ac.in/noc21_ee23/preview U University of Mumbai
Reproduced from the University of Mumbai syllabus for B.E. (Automation and Robotics) under REV-2019 'C' Scheme, in force from the academic year 2024-25. Wording is as printed in that syllabus. Module numbering is as printed there too.
The complete syllabus
This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.