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percentileNormalizer

Create percentile normalizer for anomaly map normalization

Since R2024b

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    Description

    The percentileNormalizer object creates a percentile anomaly map normalizer for a specified anomaly detector using the calculated percentile statistics of normal, or non-anomalous, images in a datastore. Use this object along with its object function normalize, to normalize anomaly score maps from different detectors to the same range, or to normalize anomaly scores for an anomaly map or a set of anomaly maps to a specified range.

    Note

    This functionality requires Deep Learning Toolbox™ and the Automated Visual Inspection Library for Computer Vision Toolbox™. You can install the Automated Visual Inspection Library for Computer Vision Toolbox from Add-On Explorer. For more information about installing add-ons, see Get and Manage Add-Ons.

    Creation

    Syntax

    normalizer = percentileNormalizer(dsNormal,detector)
    normalizer = percentileNormalizer(dsNormal,detector,Name=Value)

    Description

    normalizer = percentileNormalizer(dsNormal,detector) creates a percentile anomaly map normalizer for a specified anomaly detector, detector, using the calculated percentile statistics of normal, or non-anomalous, images in a datastore, dsNormal.

    normalizer = percentileNormalizer(dsNormal,detector,Name=Value) specifies additional options for normalization parameters using name-value arguments. For example, NormalPercentileRange=[0.95 0.99] sets the lower and upper percentile statistics range for normal images to [0.95, 0.99].

    Input Arguments

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    Normal image data, specified as a datastore that contains image data. Do not include anomalous images in this datastore.

    Anomaly detector, specified as an efficientADAnomalyDetector object, an fcddAnomalyDetector object, a fastFlowAnomalyDetector object, or a patchCoreAnomalyDetector object.

    Name-Value Arguments

    Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

    Example: percentileNormalizer(dsNormal,detector,NormalPercentileRange=[0.95 0.99]) sets the lower and upper percentile statistics range for normal images to [0.95, 0.99].

    Normal image percentile range, specified as a vector of the form [p1 p2], where p1 and p2 are the lower and upper percentile bounds, respectively. The lower and upper percentile values must be in the range [0, 1].

    p1 and p2 define the slope of the linear mapping from the anomaly score input to the normalized anomaly score values. To learn more, see Linear Mapping for Anomaly Map Normalization.

    Training progress information display in the command window, specified as a logical 1 (true) or 0 (false).

    Properties

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    Anomaly map percentile values, P1 and P2, stored as a two-element numeric vector of the form [P1 P2].

    Object Functions

    normalizeNormalize anomaly score map using percentiles

    More About

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    Version History

    Introduced in R2024b

    See Also

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    Topics