Automated System for Text Detection Individual Video Images

Abstract

Text detection in video images is a challenging research problem because of the poor spatial resolution and complex background, which may contain a variety of colors. An automated system for text detection in video images is presented. It makes use of four modules to implement a series of processes to extract text regions from video images. The first module, called the multistage pulse code modulation (MPCM) module, is used to locate potential text regions in color video images. It converts a video image to a coded image, with each pixel encoded by a priority code ranging from 7 down to 0 in accordance with its priority, and further produces a binary thresholded image, which segments potential text regions from the background. The second module, called the text region detection module, applies a sequence of spatial filters to remove noisy regions and eliminate regions that are unlikely to contain text. The third module, called the text box finding module, merges text regions and produces boxes that are likely to contain text. Finally, the fourth module, called the optical character recognition (OCR) module, eliminates the text boxes that produce no OCR output. An extensive set of experiments is conducted and demonstrates that the proposed system is effective in detecting text in a wide variety of video images.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2003
Accession Number
ADA440110

Entities

People

  • Chein-i. Chang
  • Paul D. Thouin
  • Yingzi Du

Organizations

  • University of Maryland, Baltimore County

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Change Detection
  • Character Recognition
  • Coding
  • Computer Programming
  • Computer Science
  • Control Systems
  • Detection
  • Detectors
  • Gray Scale
  • Image Processing
  • Images
  • Language
  • Modulation
  • Pulse Code Modulation
  • Recognition
  • Video
  • Video Images

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Computer Science.
  • Image Processing and Computer Vision.