PR3008 Machine Vision Syllabus:
PR3008 Machine Vision Syllabus – Anna University Regulation 2021
COURSE OBJECTIVES:
• To understand the principles and tasks of machine vision.
• To know the importance of image acquisition systems and conversion processes.
• To use the image processing techniques for decision making.
• To understand the fundamental of classifiers.
• To apply the concept of the machine vision system in Manufacturing and measurement.
UNIT I INTRODUCTION TO MACHINE VISION
Machine Vision use of machine vision – tasks for a vision system – relation to other fields – place of vision in CIM.
UNIT II IMAGE ACQUISITION AND CONVERSION
Colour systems – light sources – lighting techniques – image formation by lensing – image scanning –television cameras – sensors, charge coupled devices – camera and system interface – frame buffers and frame grabbers – digital and smart cameras.
UNIT III IMAGE PROCESSING DECISION MAKING
Processing of binary images – thresholding, geometrical properties, topological properties – processing of gray scale images statistical operations, spatial operations, segmentation edge detection, morphological operations – image analysis – factors extraction – decision making.
UNIT IV PATTERN RECOGNITION
Fundamentals – parametric classifiers – nonparametric, classifiers nearest neighbor CART, neural networks, generic classifiers.
UNIT V MACHINE VISION APPLICATIONS
Applications in user industries automotive, semiconductor, electronic manufacturing, printing industries etc. – generic applications founding manufacturing metrology, inspection assembly verification – application analysis and implementation.
TOTAL: 45 PERIODS
COURSE OUTCOMES
Upon successful completion of the course, students should be able to:
CO1: Understand the Machine vision principle.
CO2: Understand the image acquisition and conversion principle.
CO3 Understand the image processing procedures for decision making
CO4: Use machine vision techniques for pattern recognizing.
CO5: Apply machine vision concept in manufacturing industries in process implementation and assembly
TEXT BOOKS:
1. Milan Sonka, Vaclav Hlavac, Roger Boyle, “Image Processing, Analysis and Machine Vision”, Springer US, 2013.
REFERENCES:
1. Richard O.Duda, Peter E. Hurt, Pattern Classification and Scene Analysis,Johnweily Publisher,2000.
2. Rafael C. Gonzaies, Richard E. Woods, Digital Image processing, Pearson, 2009.
3. Nella Zuech, ‘Understanding & applying machine vision Marcel Dekker Inc. 2000.