Computer Graphics

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Visual Information Processing
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Human Perception V.S. Machine Perception

• Human perception
• pictorial information improvement for
  
• human interpretation
• Machine perception
• scene data processing for machine
• understanding.

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Visual Information Processing

• Why processing visual information
• - Better perception for visualization
• - Medical imaging
• - Video images (e.g., television
  commercials to feature films)
• - Storage and transmission
• - Application for machine intelligence,
  robotics, multimedia, graphics and
• human computer interaction technology
• Topics in this course
• - Image processing fundamentals
• - Image analysis
• - Motion image processing (video)
• - Object recognition
• - Application with state-of-the-art
  techniques

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Basic Concepts

• Computer Vision
• - simulate the human visual
  system, not only see the world, but also
  understand the world (emulate human vision
  analysis and understanding)
• Image Processing
• - pre-process the image for
  better see or understand
• Pattern Recognition
• - classify and recognize both
  image content and some other statistic data.
• Computer Graphics
• - create or synthesize a
  virtual image
• Artificial Intelligence
• - emulate human intelligence

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Digital Image Processing Development

• Digital image processing
• - Low-level Primitive operations (e.g.,
  contrast enhancement,
• sharpening in
  Photoshop and Photo-Stacker)
• Image-gtimage
• - Mid-level Image segmentation,
  classification
• image-gtattributes
  (e.g., edges, objects).
• - High-level Ensemble of recognized
  objects
• (vision make it
  understood)
• 1920s - Digitized newspaper picture transmitted
  through submarine cable
• (Londonlt-gtNew York)
• - 5 distinct brightness level
  -gt 15 levels

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Digital Image Processing Development (Contd)

• 1960s - Images from space probe (distortion
  correction image transform)
• 1970s - Computerized Tomography (CT) (a ring of
  detectors collect the x-rays to represent a
  slice)
• 1980s and later
• - Computer image processing in industry,
  biomedical area, military recognition, satellite
  imagery for weather and environment.
• - Development of signal processing.

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Digital Image Processing Development (Contd)
left Original image right Processed image

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Image Representation

• Image (Monochrome image / color image)
• -- f(x,y) - two-dimensional
  light intensity function
• -- (x,y) denote spatial
  coordinates
• -- the value of f at any point
  (x, y) is proportional to the brightness
• (or gray level or gray scale)
  of the image at that point.
• Example

o
y
x
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Digital Image Representation

• Digital image
• -- an image f(x,y) that has been
  discretized both in the image
• coordinates and in brightness
• -- A matrix the elements of digital
  array are called
• pixels (picture elements, image
  elements, pels)
• -- In computer programming 2D array
• -- Size width - number of pixels
  horizontally
• height number of pixels
  vertically
• Example

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Digital Image Processing System
Image Display
Computer
Hardcopy
Image Processing Software
Specialized Image Processing Hardware
(digitizer, ALU Arithmetic logic unit)
Image Sensors (optical to electronic)
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Digital Image ProcessingFundamentals
Color Image Processing
Image Compression
Multiresolution Processing
Morphological Processing
Image Restoration
Image Segmentation
Image Enhancement
Representation Description
Knowledge Base
Image Acquisition
Object Recognition
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Still Image vs.Motion image

• Still Image
• JPEG, JPEG2000
• All the fundamental processing
• Image synthesis
• Motion Image
• Motion analysis and detection
• Video processing and transmission (H.261, H.263,
  H.264, MPEG1, 2, 4, 7, 21)

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Illusion
http//www.michaelbach.de/ot/fcs_thompson-thatcher
/index.html http//members.tripod.com/RBHcognitio
ns/thatc1.htm http//www.wjh.harvard.edu/lombrozo
/home/illusions/thatcher.html
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Image Analysis- Computer Vision

• Human Vision
• - 70 information from visual
  perception
• - 30 information from sound,
  touch, taste, smell,
• Computer Vision
• - object detection (edge,
  region, texture, color,)
• - camera calibration
• - 2D to 3D (shape from shading,
  shape from texture,
• shape from motion, )

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Virtual Image- Image Synthesis

• Real Image and Virtual Image
• Image analysis real image
• - using computer to understand the real
  world
• Image Synthesis virtual image
• - using computer to create a virtual
  world (computer graphics)

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Evaluation

• Subjective and Objective Evaluation
• Subjective No better way to judge the quality of
  an image than human vision
• - rating
• Objective pixel-by-pixel comparison
• - mean square errors measurement

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Recent Development

• Characteristics
• Better quality, Fast processing, Accurate
  Detection, and More understanding
• Architecture Parallel algorithm
• Robotics and Active vision
• Face and Gesture Recognition
• Document Image Analysis
• Texture Analysis
• Motion tracking and Analysis
• Color image analysis

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Relevant areas

• Computer Graphics
• Image Processing
• Multimedia
• Human Computer Interaction/Interface

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Applications

• Biomedical area (CT images)
• Military recognition
• Satellite imagery for weather and environment
• Motion video (MPEG video)
• Still image (JPEG)
• TV and Film making

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Stereo images as seen through LCD Shutterglasses
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Image Processing Programming and tools

• MS Windows Visual C
• Unix, Linux, Irix C and C
• Intel Image Processing Library.
• Image Vision Library
• Image format information (BMP, JPEG, TIF,)

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In this Class

• You will learn
• Image Processing
  Computer Vision Basics and application
• You will do
• Programming
  Assignments, Course Project (proposal, class
  presentation, project report)
• Class attendance is required.

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References

• Text books
• (1) Digital Image
  Processing (R. Gonzales)
• (2) Computer Vision
  (L. G. Shapiro)
• Journals
• IEEE Transactions on
  Pattern Analysis and Machine Intelligence
• IEEE Transactions on
  Image Processing
• Computer vision,
  Graphics and Image Processing
• Pattern Recognition
• Conferences
• IEEE International
  Conf. on Computer Vision and Pattern Recognition
• IEEE International
  Conference on Computer Vision
• IEEE International
  Conference on Pattern Recognition
• IEEE International
  Conference on Image Processing