Feature recognition techniques

Andreas Wimmer, Iris Lingenfelder, Charles Beumier, Jordi Inglada, Simon J. Caseley

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Almost all applications of remotely sensed imagery require generic algorithms for image feature extraction and classification to gain the required information. Therefore the GMOSS project defined a work package Feature recognition to serve the application work packages in their need to derive information for their tasks. For this purpose an important task is the definition of terms, nomenclature and the creation of a feature catalogue which describes significant features as well as the ability and means to detect these features. The work performed in this work package covers a very wide area and reaches from basic image processing algorithms used in pre-processing steps to highly sophisticated automated, object-based classification and detection methods and its evaluation regarding to performance and robustness. In principle two basic operations will be covered by the feature recognition work package. Classification should provide good and robust background knowledge of the basic land-cover within a certain area whereas object detection techniques are specialized on finding one specific feature or object in a defined area.

Original languageEnglish
Title of host publicationRemote Sensing from Space
Subtitle of host publicationSupporting International Peace and Security
PublisherSpringer
Pages105-118
Number of pages14
ISBN (Print)9781402084836
DOIs
Publication statusPublished - 2009

Keywords

  • Feature recognition
  • classification
  • feature extraction
  • object detection
  • preprocessing

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