@spec averageHash(Keyword.t()) :: any() | {:error, String.t()}

@spec averageHash(Evision.Mat.maybe_mat_in()) ::
  Evision.Mat.t() | {:error, String.t()}

Calculates img_hash::AverageHash in one call

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3 or CV_8UC1.

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 16 hex decimal number, return type is CV_8U

Python prototype (for reference only):

averageHash(inputArr[, outputArr]) -> outputArr

@spec averageHash(Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil) ::
  Evision.Mat.t() | {:error, String.t()}

Calculates img_hash::AverageHash in one call

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3 or CV_8UC1.

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 16 hex decimal number, return type is CV_8U

Python prototype (for reference only):

averageHash(inputArr[, outputArr]) -> outputArr

@spec blockMeanHash(Keyword.t()) :: any() | {:error, String.t()}

@spec blockMeanHash(Evision.Mat.maybe_mat_in()) ::
  Evision.Mat.t() | {:error, String.t()}

Computes block mean hash of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3 or CV_8UC1.

Keyword Arguments

• mode: integer().

  the mode

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 16 hex decimal number, return type is CV_8U

Python prototype (for reference only):

blockMeanHash(inputArr[, outputArr[, mode]]) -> outputArr

@spec blockMeanHash(Evision.Mat.maybe_mat_in(), [{:mode, term()}] | nil) ::
  Evision.Mat.t() | {:error, String.t()}

Computes block mean hash of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3 or CV_8UC1.

Keyword Arguments

• mode: integer().

  the mode

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 16 hex decimal number, return type is CV_8U

Python prototype (for reference only):

blockMeanHash(inputArr[, outputArr[, mode]]) -> outputArr

@spec colorMomentHash(Keyword.t()) :: any() | {:error, String.t()}

@spec colorMomentHash(Evision.Mat.maybe_mat_in()) ::
  Evision.Mat.t() | {:error, String.t()}

Computes color moment hash of the input, the algorithm is come from the paper "Perceptual Hashing for Color Images Using Invariant Moments"

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3 or CV_8UC1.

Return

• outputArr: Evision.Mat.t().

  42 hash values with type CV_64F(double)

Python prototype (for reference only):

colorMomentHash(inputArr[, outputArr]) -> outputArr

@spec colorMomentHash(Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil) ::
  Evision.Mat.t() | {:error, String.t()}

Computes color moment hash of the input, the algorithm is come from the paper "Perceptual Hashing for Color Images Using Invariant Moments"

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3 or CV_8UC1.

Return

• outputArr: Evision.Mat.t().

  42 hash values with type CV_64F(double)

Python prototype (for reference only):

colorMomentHash(inputArr[, outputArr]) -> outputArr

@spec marrHildrethHash(Keyword.t()) :: any() | {:error, String.t()}

@spec marrHildrethHash(Evision.Mat.maybe_mat_in()) ::
  Evision.Mat.t() | {:error, String.t()}

Computes average hash value of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3, CV_8UC1.

Keyword Arguments

• alpha: float.

  int scale factor for marr wavelet (default=2).

• scale: float.

  int level of scale factor (default = 1)

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 16 hex decimal number, return type is CV_8U

Python prototype (for reference only):

marrHildrethHash(inputArr[, outputArr[, alpha[, scale]]]) -> outputArr

@spec marrHildrethHash(
  Evision.Mat.maybe_mat_in(),
  [alpha: term(), scale: term()] | nil
) ::
  Evision.Mat.t() | {:error, String.t()}

Computes average hash value of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3, CV_8UC1.

Keyword Arguments

• alpha: float.

  int scale factor for marr wavelet (default=2).

• scale: float.

  int level of scale factor (default = 1)

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 16 hex decimal number, return type is CV_8U

Python prototype (for reference only):

marrHildrethHash(inputArr[, outputArr[, alpha[, scale]]]) -> outputArr

@spec pHash(Keyword.t()) :: any() | {:error, String.t()}

@spec pHash(Evision.Mat.maybe_mat_in()) :: Evision.Mat.t() | {:error, String.t()}

Computes pHash value of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3, CV_8UC1.

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 8 uchar value

Python prototype (for reference only):

pHash(inputArr[, outputArr]) -> outputArr

@spec pHash(Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil) ::
  Evision.Mat.t() | {:error, String.t()}

Computes pHash value of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3, CV_8UC1.

Return

• outputArr: Evision.Mat.t().

  Hash value of input, it will contain 8 uchar value

Python prototype (for reference only):

pHash(inputArr[, outputArr]) -> outputArr

@spec radialVarianceHash(Keyword.t()) :: any() | {:error, String.t()}

@spec radialVarianceHash(Evision.Mat.maybe_mat_in()) ::
  Evision.Mat.t() | {:error, String.t()}

Computes radial variance hash of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3, CV_8UC1.

Keyword Arguments

• sigma: double.

  Gaussian kernel standard deviation

• numOfAngleLine: integer().

  The number of angles to consider

Return

• outputArr: Evision.Mat.t().

  Hash value of input

Python prototype (for reference only):

radialVarianceHash(inputArr[, outputArr[, sigma[, numOfAngleLine]]]) -> outputArr

@spec radialVarianceHash(
  Evision.Mat.maybe_mat_in(),
  [numOfAngleLine: term(), sigma: term()] | nil
) ::
  Evision.Mat.t() | {:error, String.t()}

Computes radial variance hash of the input image

Positional Arguments

• inputArr: Evision.Mat.

  input image want to compute hash value, type should be CV_8UC4, CV_8UC3, CV_8UC1.

Keyword Arguments

• sigma: double.

  Gaussian kernel standard deviation

• numOfAngleLine: integer().

  The number of angles to consider

Return

• outputArr: Evision.Mat.t().

  Hash value of input

Python prototype (for reference only):

radialVarianceHash(inputArr[, outputArr[, sigma[, numOfAngleLine]]]) -> outputArr