Digital Image Processing
TECHNICAL UNIVERSITY OF CRETE
DEPARTMENT OF ELECTRONIC AND COMPUTER ENGINEERING
MACHINE VISION
Euripides G.M. Petrakis Michalis Zervakis
http://www.intelligence.tuc/~petrakis http://courses.ece.tuc.gr
Chania 2010
E.G.M. Petrakis Machine Vision (Introduction) 1
Machine Vision
• The goal of Machine Vision is to create a model of the real world from images
– A machine vision system recovers useful information about a scene from its two dimensional projections – The world is three dimensional – Two dimensional digitized images
E.G.M. Petrakis
Machine Vision (Introduction)
2
Machine Vision (2)
• Knowledge about the objects (regions) in a scene and projection geometry is required. • The information which is recovered differs depending on the application
– Satellite, medical images etc.
• Processing takes place in stages:
– Enhancement, segmentation, image analysis and matching (pattern recognition).
E.G.M. Petrakis Machine Vision (Introduction) 3
Illumination
Image Acquisition
Machine Vision System
Scene
2D Digital Image
Image Description
Feedback The goal of a machine vision system is to compute a meaningful description of the scene (e.g., object)
Machine Vision Stages
Image Acquisition (by cameras, scanners etc) Image Processing Image Enhancement Image Restoration
• Analog to digital conversion • Remove noise/patterns, improve contrast • Find regions (objects) in the image • Take measurements of objects/relationships • Match the above description with similar description of known objects (models)
5
Image Segmentation
Image Analysis (Binary Image Processing) Model Matching Pattern Recognition E.G.M. Petrakis
Machine Vision (Introduction)
Image Processing
Image Processing
Input Image
Output Image
• Image transformation – image enhancement (filtering, edge detection, surface detection, computation of depth). – Image restoration (remove point/pattern degradation: there exist a
DEPARTMENT OF ELECTRONIC AND COMPUTER ENGINEERING
MACHINE VISION
Euripides G.M. Petrakis Michalis Zervakis
http://www.intelligence.tuc/~petrakis http://courses.ece.tuc.gr
Chania 2010
E.G.M. Petrakis Machine Vision (Introduction) 1
Machine Vision
• The goal of Machine Vision is to create a model of the real world from images
– A machine vision system recovers useful information about a scene from its two dimensional projections – The world is three dimensional – Two dimensional digitized images
E.G.M. Petrakis
Machine Vision (Introduction)
2
Machine Vision (2)
• Knowledge about the objects (regions) in a scene and projection geometry is required. • The information which is recovered differs depending on the application
– Satellite, medical images etc.
• Processing takes place in stages:
– Enhancement, segmentation, image analysis and matching (pattern recognition).
E.G.M. Petrakis Machine Vision (Introduction) 3
Illumination
Image Acquisition
Machine Vision System
Scene
2D Digital Image
Image Description
Feedback The goal of a machine vision system is to compute a meaningful description of the scene (e.g., object)
Machine Vision Stages
Image Acquisition (by cameras, scanners etc) Image Processing Image Enhancement Image Restoration
• Analog to digital conversion • Remove noise/patterns, improve contrast • Find regions (objects) in the image • Take measurements of objects/relationships • Match the above description with similar description of known objects (models)
5
Image Segmentation
Image Analysis (Binary Image Processing) Model Matching Pattern Recognition E.G.M. Petrakis
Machine Vision (Introduction)
Image Processing
Image Processing
Input Image
Output Image
• Image transformation – image enhancement (filtering, edge detection, surface detection, computation of depth). – Image restoration (remove point/pattern degradation: there exist a
Bibliography: • “Machine Vision”, Ramesh Jain, Rangachar Kasturi, Brian G. Schunck, Mc Graw-Hill, 1995 (highly recommended!). • "Machine Vision, Theory, Algorithms, Practicalities ' ', E. R. Davies, Academic Press, 1997.