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Home / Syllabus / B.E. (Computer Engineering) / Fourth Year CE / Semester 7 / Machine Vision

B.E. (Computer Engineering) Machine Vision 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.

Machine-Vision.pdf
Semester 7 · Fourth Year CE

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Syllabus for Machine Vision

Semester 7 · Fourth Year CE

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, Monochrome and Color 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-Neighbor 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

Module 4: Digital Image Processing for Machine Vision Applications

  • Preprocessing., Image Filtering, Normalized Box Filter Gaussian Filter Bilateral Filter, Comparison of Filter Techniques, Sub sampling/Scaling Histogram, Image Segmentation, Threshold Based Segmentation Edge-Based Segmentation First-Order Derivative Edge Detection. Second-Order Derivative Operators, Comparison of Edge Detection Techniques, Region-Based Segmentation Region Growing Methods, Region Split and Merge Method, Morphological Image Processing: Dilation, Erosion, Opening, Closing, Hit-or-Miss transformation, Object Recognition. Template Matching. Blob Analysis

Module 5: Motion Analysis

  • Differential motion Analysis, Optical Flow, Analysis based on correspondence of interest points, Detection of specific motion Patterns, Video Tracking

Module 6: Emerging Trends in Machine Vision

  • History of Industrial Revolution(s), Machine Vision and
  • 6.1 Industry 4.0, Emerging Vision Trends in Manufacturing, 3D Imaging, Emerging Vision Trends in Manufacturing, Applications in Machine/ Computer Vision: Face detection, 6.2 face recognition, eigen faces, car on roads

Useful Links

  • 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 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 Chiranji Lal Chowdhary, Mamoun Alazab, Ankit Chaudhary, SaqibHakak 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 OpenCV 3 Computer Vision with Python”, Second Edition, Packt Publishing Ltd.
  • 3 Alexander Hornberg,, “ Handbook of Machine and Computer Vision The Guide for Developers and Users,
  • 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

Reproduced from the University of Mumbai syllabus for B.E. (Computer Engineering) under REV-2019 'C' Scheme, in force from the academic year 2022-23. 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.

PDF 7.9 (R-A) B.E. (Computer Engineering) Sem I & II (Revised, NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.24 (N) B.E. (Computer Engineering) Sem III & IV (NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.15 B.E. (Computer Engineering) Third Year, Sem V & VI (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
PDF 6.41 (R) B.E. (Computer Engineering) Fourth Year, Sem VII & VIII (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
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