Image and Signal Processing Methods

Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?

[+] Author Affiliations
Andreja Švab Lenarčič, Nataša Đurić, Klemen Čotar

Slovenian Centre of Excellence for Space Sciences and Technologies, Aškerčeva cesta 12, SI-1000 Ljubljana, Slovenia

Klemen Ritlop

University of Ljubljana, Faculty of Civil and Geodetic Engineering, Jamova cesta 2, SI-1000 Ljubljana, Slovenia

Krištof Oštir

University of Ljubljana, Faculty of Civil and Geodetic Engineering, Jamova cesta 2, SI-1000 Ljubljana, Slovenia

Research Centre of the Slovenian Academy of Sciences and Arts, Novi trg 2, SI-1000 Ljubljana, Slovenia

J. Appl. Remote Sens. 10(4), 045010 (Oct 24, 2016). doi:10.1117/1.JRS.10.045010
History: Received June 14, 2016; Accepted October 5, 2016
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Abstract.  It is a broadly established belief that the segmentation result significantly affects subsequent image classification accuracy. However, the actual correlation between the two has never been evaluated. Such an evaluation would be of considerable importance for any attempts to automate the object-based classification process, as it would reduce the amount of user intervention required to fine-tune the segmentation parameters. We conducted an assessment of segmentation and classification by analyzing 100 different segmentation parameter combinations, 3 classifiers, 5 land cover classes, 20 segmentation evaluation metrics, and 7 classification accuracy measures. The reliability definition of segmentation evaluation metrics as indicators of land cover classification accuracy was based on the linear correlation between the two. All unsupervised metrics that are not based on number of segments have a very strong correlation with all classification measures and are therefore reliable as indicators of land cover classification accuracy. On the other hand, correlation at supervised metrics is dependent on so many factors that it cannot be trusted as a reliable classification quality indicator. Algorithms for land cover classification studied in this paper are widely used; therefore, presented results are applicable to a wider area.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Andreja Švab Lenarčič ; Nataša Đurić ; Klemen Čotar ; Klemen Ritlop and Krištof Oštir
"Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?", J. Appl. Remote Sens. 10(4), 045010 (Oct 24, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.045010


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