Compare two segmentations with Hoover metrics
This application compares a machine segmentation (MS) with a partial ground truth segmentation
(GT). The Hoover metrics are used to estimate scores for correct detection, over-segmentation,
under-segmentation and missed detection.
The application can output the overall Hoover scores along with coloredimages of the MS and GT
segmentation showing the state of each region (correct detection, over-segmentation, under-segmentation,
missed)
The Hoover metrics are described in : Hoover et al., ”An experimental comparison of range image
segmentation algorithms”, IEEE PAMI vol. 18, no. 7, July 1996.
This section describes in details the parameters available for this application. Table 5.65, page 681 presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is HooverCompareSegmentation.
Parameter key | Parameter type |
Parameter description |
ingt | Input image |
Input ground truth |
inms | Input image |
Input machine segmentation |
bg | Int |
Background label |
th | Float |
Overlapping threshold |
outgt | Output image |
Colored ground truth output |
outms | Output image |
Colored machine segmentation output |
rc | Float |
Correct detection score |
rf | Float |
Over-segmentation score |
ra | Float |
Under-segmentation score |
rm | Float |
Missed detection score |
inxml | XML input parameters file |
Load otb application from xml file |
outxml | XML output parameters file |
Save otb application to xml file |
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To run this example in command-line, use the following:
To run this example from Python, use the following code snippet:
None
This application has been written by OTB-Team.
These additional ressources can be useful for further information: