# HooverCompareSegmentation

## Brief Description

Compare two segmentations with Hoover metrics

## Tags

Segmentation

## Long Description

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.

## Parameters

- [param] -ingt <string> A partial ground truth segmentation image.. Mandatory: True. Default Value: ""
- [param] -inms <string> A machine segmentation image.. Mandatory: True. Default Value: ""
- [param] -bg <int32> Label value of the background in the input segmentations. Mandatory: True. Default Value: "0"
- [param] -th <float> Overlapping threshold used to find Hoover instances.. Mandatory: True. Default Value: "0.75"
- [param] -outgt <string> The colored ground truth output image.. Mandatory: False. Default Value: ""
- [param] -outms <string> The colored machine segmentation output image.. Mandatory: False. Default Value: ""
- [param] -rc <float> Overall score for correct detection (RC). Mandatory: True. Default Value: "0.0"
- [param] -rf <float> Overall score for over segmentation (RF). Mandatory: True. Default Value: "0.0"
- [param] -ra <float> Overall score for under segmentation (RA). Mandatory: True. Default Value: "0.0"
- [param] -rm <float> Overall score for missed detection (RM). Mandatory: True. Default Value: "0.0"

## Limitations

None

## Authors

OTB-Team

## See Also

otbHooverMatrixFilter, otbHooverInstanceFilter, otbLabelMapToAttributeImageFilter

## Example of use

- ingt: maur_GT.tif

- inms: maur_labelled.tif

- outgt: maur_colored_GT.tif uint8