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

Andreja Švab Lenarčič; Nataša Đurić; Klemen Čotar; Klemen Ritlop; Krištof Oštir

doi:10.1117/1.JRS.10.045010

24 October 2016 Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?

Andreja Švab Lenarčič, Nataša Đurić, Klemen Čotar, Klemen Ritlop, Krištof Oštir

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 10, Issue 4, 045010 (October 2016). https://doi.org/10.1117/1.JRS.10.045010

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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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?," Journal of Applied Remote Sensing 10(4), 045010 (24 October 2016). https://doi.org/10.1117/1.JRS.10.045010

Published: 24 October 2016

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KEYWORDS

Image segmentation

Image classification

Accuracy assessment

Image quality

Quality measurement

Reliability

Image processing

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