Anna University Syllabus - Anna University ME Syllabus
MR7202 MACHINE VISION Syllabus | Anna University ME Mechatronics Engineering Second Semester Syllabus Regulation 2013. Below is the Anna University 2013 Regulation Syllabus for 2nd Semester for ME Mechatronics engineering, Textbooks, Reference books, Exam portions, Question Bank, Previous year question papers, Model question papers, Class notes, Important 2 marks, 8 marks, 16 marks topics.
It is applicable for all students admitted in the Academic year 2013-2014 onwards for all its Affiliated institutions in Tamil Nadu.
Anna University Chennai Syllabus
MR7202 MACHINE VISION L T P C 3 0 0 3
AIM:
To impart knowledge on imaging, machine vision and its applications.
OBJECTIVES:
To understand and apply the basic concepts of optics in imaging. To learn the various
hardware components of an imaging system for machine vision applications. To understand
the various image processing and image analysis algorithms and the issues involved in
applying them to various machine vision applications. To expose students to various
applications of vision and challenges involved in each.
UNIT I INTRODUCTION 8
Human vision – Machine vision and Computer vision – Benefits of machine vision – Block diagram
and function of machine vision system implementation of industrial machine vision system –
Physics of Light – Interactions of light – Refraction at a spherical surface – Thin Lens Equation
UNIT II IMAGE ACQUISITION 12
Scene constraints – Lighting parameters – Lighting sources, Selection – Lighting Techniques –
Types and Selection – Machine Vision Lenses and Optical Filters, Specifications and Selection –
Imaging Sensors – CCD and CMOS, Specifications – Interface Architectures – Analog and Digital
Cameras – Digital Camera Interfaces – Camera Computer Interfaces, Specifications and Selection
– Geometrical Image formation models – Camera Calibration
10
UNIT III IMAGE PROCESSING 10
Machine Vision Software – Fundamentals of Digital Image – Image Acquisition Modes – Image
Processing in Spatial and Frequency Domain – Point Operation, Thresholding, Grayscale
Stretching – Neighborhood Operations, Image Smoothing and Sharpening – Edge Detection –
Binary Morphology – Color image processing.
UNIT IV IMAGE ANALYSIS 6
Feature extraction – Region Features, Shape and Size features – Texture Analysis – Template
Matching and Classification – 3D Machine Vision Techniques – Decision Making.
UNIT V MACHINE VISION APPLICATIONS 9
Machine vision applications in manufacturing, electronics, printing, pharmaceutical, textile,
applications in non-visible spectrum, metrology and gauging,OCR and OCV, vision guided robotics
– Field and Service Applications – Agricultural, and Bio medical field, augmented reality,
surveillance, bio-metrics.
TOTAL: 45 PERIODS
REFERENCES
1. EmanueleTrucco, Alessandro Verri, “Introductory Techniques For 3D Computer Vision”, First
Edition, 2009
2. Rafael C.Gonzales, Richard.E.Woods, “Digital Image Processing Publishers”, Third Edition,
2007
3. Alexander Hornberg, “Handbook of Machine Vision”, First Edition,2006
4. Eugene Hecht, A.R. Ganesan “Optics”, Fourth Edition, 2001
AIM:
To impart knowledge on imaging, machine vision and its applications.
OBJECTIVES:
To understand and apply the basic concepts of optics in imaging. To learn the various
hardware components of an imaging system for machine vision applications. To understand
the various image processing and image analysis algorithms and the issues involved in
applying them to various machine vision applications. To expose students to various
applications of vision and challenges involved in each.
UNIT I INTRODUCTION 8
Human vision – Machine vision and Computer vision – Benefits of machine vision – Block diagram
and function of machine vision system implementation of industrial machine vision system –
Physics of Light – Interactions of light – Refraction at a spherical surface – Thin Lens Equation
UNIT II IMAGE ACQUISITION 12
Scene constraints – Lighting parameters – Lighting sources, Selection – Lighting Techniques –
Types and Selection – Machine Vision Lenses and Optical Filters, Specifications and Selection –
Imaging Sensors – CCD and CMOS, Specifications – Interface Architectures – Analog and Digital
Cameras – Digital Camera Interfaces – Camera Computer Interfaces, Specifications and Selection
– Geometrical Image formation models – Camera Calibration
10
UNIT III IMAGE PROCESSING 10
Machine Vision Software – Fundamentals of Digital Image – Image Acquisition Modes – Image
Processing in Spatial and Frequency Domain – Point Operation, Thresholding, Grayscale
Stretching – Neighborhood Operations, Image Smoothing and Sharpening – Edge Detection –
Binary Morphology – Color image processing.
UNIT IV IMAGE ANALYSIS 6
Feature extraction – Region Features, Shape and Size features – Texture Analysis – Template
Matching and Classification – 3D Machine Vision Techniques – Decision Making.
UNIT V MACHINE VISION APPLICATIONS 9
Machine vision applications in manufacturing, electronics, printing, pharmaceutical, textile,
applications in non-visible spectrum, metrology and gauging,OCR and OCV, vision guided robotics
– Field and Service Applications – Agricultural, and Bio medical field, augmented reality,
surveillance, bio-metrics.
TOTAL: 45 PERIODS
REFERENCES
1. EmanueleTrucco, Alessandro Verri, “Introductory Techniques For 3D Computer Vision”, First
Edition, 2009
2. Rafael C.Gonzales, Richard.E.Woods, “Digital Image Processing Publishers”, Third Edition,
2007
3. Alexander Hornberg, “Handbook of Machine Vision”, First Edition,2006
4. Eugene Hecht, A.R. Ganesan “Optics”, Fourth Edition, 2001
No comments:
Post a Comment
Any doubt ??? Just throw it Here...