Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis

Abstract

Different methods for automatic detection of line objects applied to aerial images to extract streets from urban scenes are investigated. First, test results achieved from two existing methods of low level iconic image processing by stream following (line tracking) and structured parallel operations (image filtering, feature extraction) are given. Second, a medium level iconic image processing method developed for edge and area segmentation is described and results from image segmentation are presented symbolically. Then two preliminary approaches of high level symbolic processing by knowledge based blackboard oriented structure analysis are tested. One is originating with preprocessing by low level edge filtering, the other by medium level area segmentation. First results from the image understanding method for street network extraction are presented. Keywords: Geodesy, Images, Optics, Artificial intelligence, Automation, Line network extraction, Aerial imagery of urban areas, Mapping, Extraction of line objects, Phoenix, Bietigheim.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1989
Accession Number
ADA222675

Entities

People

  • B. Nicolin
  • H. Fueger
  • H. Kazmierczak
  • K. Jurkiewicz
  • W. Ott

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Computer Programming
  • Computer Programs
  • Computer Vision
  • Computers
  • Contracts
  • Databases
  • Feature Extraction
  • Image Processing
  • New York
  • Parallel Computing
  • Parallel Processing
  • Production Models
  • Recognition
  • Reliability
  • Standards
  • United States
  • Urban Areas

Fields of Study

  • Engineering

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Image Processing and Computer Vision.
  • Urban Planning and Geography.

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval