{"id":169738,"date":"2024-03-27T12:15:08","date_gmt":"2024-03-27T06:45:08","guid":{"rendered":"https:\/\/www.aplustopper.com\/?p=169738"},"modified":"2024-03-27T12:50:22","modified_gmt":"2024-03-27T07:20:22","slug":"mr3701-machine-vision-systems-syllabus","status":"publish","type":"post","link":"https:\/\/www.aplustopper.com\/mr3701-machine-vision-systems-syllabus\/","title":{"rendered":"MR3701 – Machine Vision Systems Syllabus Regulation 2021 Anna University"},"content":{"rendered":"

This article is about the subject code MR3701 – Machine Vision Systems Syllabus<\/a> from Anna University based on regulation 2021 relating to affiliated institutions awarding B.E Mechatronics Engineering semester VII subjects. Let’s see…<\/p>\n

We tried our best to provide the details of the subject its main concept, and the unit-wise syllabus to help you to refer the concepts from syllabus according to weightage. We have taken advice from expert faculty regarding the textbooks and references. I hope this information is useful. Kindly share it with your classmates.<\/p>\n

If you want to know more about the syllabus of B.E Mechatronics Engineering connected to an affiliated institution\u2019s four-year undergraduate degree program. We provide you with a detailed Year-wise, semester-wise, and Subject-wise syllabus in the following link B.E. Mechatronics Engineering Syllabus Regulation 2021 Anna University.<\/a><\/p>\n

Aim Of Concept:<\/strong><\/p>\n

    \n
  1. To introduce the various concepts in machine vision<\/li>\n
  2. To understand the concepts in image acquisition<\/li>\n
  3. To learn about a various basics in image processing<\/li>\n
  4. To knowledge about the feature extraction and vision techniques<\/li>\n
  5. To understand the various applications in machine vision<\/li>\n<\/ol>\n

    MR3701 – Machine Vision Systems Syllabus<\/strong><\/p>\n

    Unit I:<\/strong> Introduction<\/p>\n

    Human vision \u2013 Machine vision and Computer vision \u2013 Benefits of machine vision \u2013 Block diagram and function of machine vision system implementation of industrial machine vision system \u2013 Physics of Light \u2013 Interactions of light \u2013 Refraction at a spherical surface \u2013 Thin Lens Equation<\/p>\n

    Unit II:<\/strong> Image Acquisition<\/p>\n

    Scene constraints \u2013 Lighting parameters \u2013 Lighting sources, Selection \u2013 Lighting Techniques \u2013 Types and Selection \u2013 Machine Vision Lenses and Optical Filters, Specifications and Selection \u2013 Imaging Sensors \u2013 CCD and CMOS, Specifications \u2013 Interface Architectures \u2013 Analog and Digital Cameras \u2013 Digital Camera Interfaces \u2013 Camera Computer Interfaces, Specifications and Selection \u2013 Geometrical Image formation models \u2013 Camera Calibration<\/p>\n

    Unit III:<\/strong> Image Processing<\/p>\n

    Machine Vision Software \u2013 Fundamentals of Digital Image \u2013 Image Acquisition Modes \u2013 Image Processing in Spatial and Frequency Domain \u2013 Point Operation, Thresholding, Grayscale Stretching \u2013 Neighborhood Operations, Image Smoothing and Sharpening \u2013 Edge Detection \u2013 Binary Morphology \u2013 Colour image processing.<\/p>\n

    Unit IV:<\/strong> Feature Extraction<\/p>\n

    Feature extraction \u2013 Region Features, Shape and Size features \u2013 Texture Analysis \u2013 Template Matching and Classification \u2013 3D Machine Vision Techniques \u2013 Decision Making.<\/p>\n

    \"MR3701<\/p>\n

    Unit V:<\/strong> Machine Vision Applications<\/p>\n

    Machine vision applications in manufacturing, electronics, printing, pharmaceutical, textile, applications in non-visible spectrum, metrology and gauging, OCR and OCV, vision guided robotics \u2013 Field and Service Applications \u2013 Agricultural, and Bio medical field, augmented reality, surveillance, bio-metrics.<\/p>\n

    Text Books:<\/strong><\/p>\n

      \n
    1. Eugene Hecht, A. R. Ganesan \u201cOptics\u201d, Fourth Edition, 2008<\/li>\n
    2. Alexander Hornberg, \u201cHandbook of Machine Vision\u201d, First Edition, 2006<\/li>\n<\/ol>\n

      References:<\/strong><\/p>\n

        \n
      1. Emanuele Trucco, Alessandro Verri, \u201cIntroductory Techniques For 3D Computer Vision\u201d, First Edition, 1998<\/li>\n
      2. Rafael C. Gonzales, Richard. E. Woods, \u201cDigital Image Processing Publishers\u201d, Fourth Edition, 1992<\/li>\n<\/ol>\n

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