Computer Vision

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Computer Vision

• Ronald Frazier
• CIS 479
• April 20, 1999

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Introduction

• Important area of study
• Ease of use for new users
• Managing large quantities of images

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Combines a Variety of Disciplines

• Standard Programming Techniques
• Artificial Intelligence Techniques
• Neural Networks
• Fuzzy Logic
• Image Processing Techniques
• Human Biology and Physiology

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Optical Character Recognition (OCR)

• Converting graphical representation of text to
  character based representation
• One of the most developed areas of computer
  vision
• Lots of ideas for further research

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OCR - Character Recognition

• Examining graphical representation of character
  to determine character represented
• Identification Process
• Apply image processing
• Identify character (usually using neural networks)

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OCR - Sample Character Recognition Algorithm

• Calculate average slope and curvature for each
  cell

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OCR - Sample Character Recognition Algorithm

• Chaincode Algorithm

• Data processed by Neural Network
• Character recognized by Neural Network

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Types of OCR

• Preprinted Text
• Live Handwriting

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OCR - Preprinted Text

• Text that has already been written or typed
  before recognition begins
• ex Encyclopedia, Contract, Report
• Can be used on printed or handwritten documents

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OCR - Preprinted Text

• Recognition Process
• Identify possible individual characters
• Standard character recognition techniques
• determine possible words
• Compare to dictionary and determine existing
  words
• Select most likely existing word

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Applications - U.S. Postal Service

• Handle over 100 billion parcels yearly.
• Need automated way to identify destination of
  each parcel and print a barcode for faster
  processing.
• For more details, see my web site

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OCR - Live Handwriting

• Process text as it is written
• ex Personal Digital Assistants
• Can be used on handwritten documents
• Track time, direction, and angles of lines as
  they are written and use it to identify character

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Content Based Image Recognition (CBIR)

• Identifying contents of images
• Applications
• Automated organization and classification of
  images
• Image database searching
• Still images or video

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CBIR - Recognition Methods

• Content that can be recognized
• Specific colors and approximate proportions
• ex A lot of Red, a little bit of Green
• Objects base on shapes, colors, textures, edges,
  size, etc.
• Face detection

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Applications - News Video Recognition and
Retrieval

• Store video in database along with description of
  content for searching
• Automated determination of video content

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Applications - News Video Recognition and
Retrieval

• Processing Technique
• locate and extract on screen captions and closed
  captions
• Apply OCR to convert captions to text

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Applications - News Video Recognition and
Retrieval

• Processing Difficulties
• Interference from background image
• Handled by Frame Filtering and Frame ANDing
• Low resolution of captions
• Handled by magnifying characters and
  interpolating pixel values

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Other Possible Uses of Computer Vision

• Robots
• Self-Controlled Vehicles
• Security - Fingerprint and Retina Matching

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Additional Information

• For more information on additional topics not
  covered in this presentation, along with links to
  other computer vision pages, see my web site at
• http//people.mw.mediaone.net/ldkronos/AI