Introduction to Image Processing Grass Sky Tree ? ? Introduction A picture is worth more than a thousand words

Aims and Objectives A general introduction to the common techniques of image processing and its relations with Computer Vision and Computer Graphics To review and understand the principal approaches used, which provide as the basis for further study of the related fields To offer practical experience in writing programs that manipulate images, using examples in Java

Module Information Prerequisites: G51MCS, G51PRG or equivalent Course Structure –Lecture: 2 hours/week –Practical: 1 hour/week (starting week 3/4) Assessment –Programming Assignment (40%) –1-hour exam (60%) Handouts OR /G52IIP/ Reference Books –Digital Image Processing, 3 rd Edition by Rafael Gonzalez & Richard Woods –Digital Image Processing Using Java by Nick Efford

Image Processing, Vision, Graphics In image processing we do things like –removing noise from images –finding edges and features in images –generally changing 2D images to other 2D images In computer vision we do things like –finding moving objects in a scene –recognising objects from a database –build abstract models of the world from images –generally extract information about 3D world from 2D images In computer graphics we do things like –creating a 3D model, with realistic shape, colour, texture, and project it to 2D for viewing –animate the 3D model –creating a virtual world and animate the objects in it The link between imaging and graphics –image based modelling

Computer Graphics (Courtesy of Michael Cohen) Image Output Model Synthetic Camera

Real Scene Computer Vision Real Cameras Model Output (Courtesy of Michael Cohen)

Vision and Graphics Combined Model Real Scene Real Cameras Image Output Synthetic Camera (Courtesy of Michael Cohen)

Image Processing (1) Image Enhancement Image Restoration

Image Processing (2) Image Compression

Computer Vision: Recognition

Another Useful Paradigm Three Processing Levels:  Low-level process: –primitive operations like noise reduction, contrast enhancement, image sharpening… –input: image output: image  Mid-level process: –tasks like segmentation, representation, description –input: image output: attributes extracted from images  High-level process –“making sense” of an ensemble of recognized objects –input: image (sequence) output: interpretation Digital Image Processing Computer Vision

Proposed Contents Fundamentals Basic Image Manipulation Noise and Spatial Techniques Point, Line & Edge Detection Image Segmentation & Representation Basic Spectral Techniques Others if time permits

Words of Caution Lecture Contents  slightly mathematical + practical  attendance required to understand lecture materials  not difficult but leaving it until the last minute can be disastrous  further readings are required if you intend to undertake DIP related projects Reference Texts  read them if you need more detailed explanations than what is found in the lecture slides Tips for Passing this Module  coursework must be submitted  practise by solving the past exam questions  show detailed steps of how the final answers are derived in your answer scripts

Light and Colour The spectrum of electromagnetic waves:

Radio Images kneespinehead visible infraredradio Radio Band − medicine and astronomy

Radar Images mountains in southeast Tibet Microwave Band

Thermal Images human body disperses heat (red pixels) different colours indicate varying temperatures Infrared Band

Remote Sensing hurricane Andrew taken by NOAA GEOS America at night (Nov. 27, 2000) V isible and Infrared Bands − weather and environmental observations

Light Microscopy taxol (250  ) cholesterol (40  )microprocessor (60  ) V isible Band − pharmaceuticals and microinspection

Fluorescence Microscopy normal cornsmut corn U ltraviolet Band

X-Ray Imaging chesthead

Gamma-Ray Imaging positron emission tomography Cygnus Loop in the constellation of Cygnus

Other Non-Electromagnetic Imaging Modalities Acoustic Imaging  translate “ sound waves ” into image signals Electron Microscopy  shine a beam of electrons through a specimen Synthetic Images in Computer Graphics  computer generated (non-existent in the real world)

Application Areas Space  cosmic radiation, images from Hubble space telescope and interplanetary probe Medicine  multitude of diagnostic medical images Remote Sensing and GIS  terrain classification and meteorology Industrial Inspection  replace human operators with machines Security and Law Enforcement  surveillance and biometrics Human Computer Interaction  more natural interface using face, gesture recognition

Acknowlegements Slides are modified based on the original slide set from Dr Li Bai, The University of Nottingham, Jubilee Campus plus adoptions from the following sources: Digital Image Processing book by Gonzalez and Woods robots.stanford.edu/cs223b07/notes/CS223B-L1- Intro.ppt nia/prez/TEI/bebis/CV_Overview.ppt