SlideServe
Télécharger Obtenir Pro
Menu
Accueil Pro
Préférences
ApparenceLight Aide et commentaires
© SlideServe · v2026

Introduction to Computer Vision and Optical Character Recognition Techniques

dino avatar
dino
19 diapositives · 410 Views · Sep 05, 2014

This document provides an overview of computer vision, focusing on its significance and ease of use for newcomers. It discusses key techniques such as Optical Character Recognition (OCR), which transforms graphical text representations into character-based output, and explores various algorithms like Chaincode for character recognition. The document also touches on applications of OCR in automated systems, including the U.S. Postal Service and personal digital assistants, as well as content-based image recognition (CBIR) and its uses in automated classification and retrieval of images.

#introduction to computer vision and optical character recognition techniques #introduction to computer vision and optical character recognition techniques ppt #powerpoint #presentation
Introduction to Computer Vision and Optical Character Recognition Techniques - slide 1
01 / 19Introduction to Computer Vision and Optical Character Recognition Techniques
1 / 17

Télécharger la présentation

Introduction to Computer Vision and Optical Character Recognition Techniques
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation

  1. Computer Vision Ronald Frazier CIS 479 April 20, 1999

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

  3. Combines a Variety of Disciplines • Standard Programming Techniques • Artificial Intelligence Techniques • Neural Networks • Fuzzy Logic • Image Processing Techniques • Human Biology and Physiology

  4. 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

  5. OCR - Character Recognition • Examining graphical representation of character to determine character represented • Identification Process • Apply image processing • Identify character (usually using neural networks)

  6. Chaincode Algorithm • Apply image processing to get outline • Break character into 4x4 grid OCR - Sample Character Recognition Algorithm • Calculate average slope and curvature for each cell

  7. OCR - Sample Character Recognition Algorithm • Chaincode Algorithm • Data processed by Neural Network • Character recognized by Neural Network

  8. Types of OCR • Preprinted Text • Live Handwriting

  9. 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

  10. 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

  11. 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

  12. 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

  13. Content Based Image Recognition (CBIR) • Identifying contents of images • Applications • Automated organization and classification of images • Image database searching • Still images or video

  14. 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

  15. Applications - News Video Recognition and Retrieval • Store video in database along with description of content for searching • Automated determination of video content

  16. Applications - News Video Recognition and Retrieval • Processing Technique • locate and extract on screen captions and closed captions • Apply OCR to convert captions to text

  17. 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

  18. Other Possible Uses of Computer Vision • Robots • Self-Controlled Vehicles • Security - Fingerprint and Retina Matching

  19. 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