class cv::ThinPlateSplineShapeTransformer

Overview

Definition of the transformation. More…

#include <shape_transformer.hpp>

class ThinPlateSplineShapeTransformer: public cv::ShapeTransformer
{
public:
    // methods

    virtual
    double
    getRegularizationParameter() const = 0;

    virtual
    void
    setRegularizationParameter(double beta) = 0;
};

Inherited Members

public:
    // methods

    virtual
    void
    clear();

    virtual
    bool
    empty() const;

    virtual
    String
    getDefaultName() const;

    virtual
    void
    read(const FileNode& fn);

    virtual
    void
    save(const String& filename) const;

    virtual
    void
    write(FileStorage& fs) const;

    template <typename _Tp>
    static
    Ptr<_Tp>
    load(
        const String& filename,
        const String& objname = String()
        );

    template <typename _Tp>
    static
    Ptr<_Tp>
    loadFromString(
        const String& strModel,
        const String& objname = String()
        );

    template <typename _Tp>
    static
    Ptr<_Tp>
    read(const FileNode& fn);

    virtual
    float
    applyTransformation(
        InputArray input,
        OutputArray output = noArray()
        ) = 0;

    virtual
    void
    estimateTransformation(
        InputArray transformingShape,
        InputArray targetShape,
        std::vector<DMatch>& matches
        ) = 0;

    virtual
    void
    warpImage(
        InputArray transformingImage,
        OutputArray output,
        int flags = INTER_LINEAR,
        int borderMode = BORDER_CONSTANT,
        const Scalar& borderValue = Scalar()
        ) const = 0;

protected:
    // methods

    void
    writeFormat(FileStorage& fs) const;

Detailed Documentation

Definition of the transformation.

ocupied in the paper “Principal Warps: Thin-Plate Splines and Decomposition of Deformations”, by F.L. Bookstein (PAMI 1989). :

Methods

virtual
void
setRegularizationParameter(double beta) = 0

Set the regularization parameter for relaxing the exact interpolation requirements of the TPS algorithm.

Parameters:

beta	value of the regularization parameter.