Back to Adaptive Vision Studio website
You are here: Start » Filter Reference » Histogram Metrics » HistogramIntersection
Calculate normalized histogram intersection norm
Name | Type | Description | |
---|---|---|---|
![]() |
inHistogram1 | Histogram | First input histogram |
![]() |
inHistogram2 | Histogram | Second input histogram |
![]() |
outHistIntersection | Real |
Description
The operation computes the normalized histogram intersection defined as: \[\frac{ {\sum\limits_{j = 1}^n {\min \left( {inHistogram{1_j},inHistogram{2_j} } \right)} } }{ {\sum\limits_{j = 1}^n {inHistogram{2_j} } } }\]
Remarks
- Data sets for the input histograms cannot be empty, otherwise an error with appropriate description occurs,
- inHistogram1 and inHistogram2 must have the same BinSizes, otherwise an error with appropriate description occurs.
Errors
This filter can throw an exception to report error. Read how to deal with errors here: Error Handling
Error type | Description |
---|---|
DomainError | Input histogram1 is empty or has negative bins in HistogramIntersection. |
DomainError | Input histogram2 is empty or has negative bins in HistogramIntersection. |
DomainError | Input histograms formats are not the same in HistogramIntersection. |
Complexity Level
This filter is available on Basic Complexity Level.