Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors
Li, Zhengrong, Liu, Yuee, Hayward, Ross, & Walker, Rodney (2010) Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Part A), ISPRS, Vienna, Austria, pp. 128-133.
This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.
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|Item Type:||Conference Paper|
|Keywords:||Classification, Texture Feature, Machine Learning, Object-based Image Analysis, Vegetation|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > GEOMATIC ENGINEERING (090900) > Photogrammetry and Remote Sensing (090905)
|Divisions:||Current > Research Centres > Australian Research Centre for Aerospace Automation
Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Engineering Systems
|Deposited On:||20 Dec 2010 04:16|
|Last Modified:||29 Feb 2012 14:31|
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