opencv-0.0.0.0: Haskell binding to OpenCV-3.x

Safe HaskellNone
LanguageHaskell2010

OpenCV.ImgProc.ImgFiltering

Description

Functions and classes described in this section are used to perform various linear or non-linear filtering operations on 2D images (represented as Mat's). It means that for each pixel location (x,y) in the source image (normally, rectangular), its neighborhood is considered and used to compute the response. In case of a linear filter, it is a weighted sum of pixel values. In case of morphological operations, it is the minimum or maximum values, and so on. The computed response is stored in the destination image at the same location (x,y). It means that the output image will be of the same size as the input image. Normally, the functions support multi-channel arrays, in which case every channel is processed independently. Therefore, the output image will also have the same number of channels as the input one.

Another common feature of the functions and classes described in this section is that, unlike simple arithmetic functions, they need to extrapolate values of some non-existing pixels. For example, if you want to smooth an image using a Gaussian 3x3 filter, then, when processing the left-most pixels in each row, you need pixels to the left of them, that is, outside of the image. You can let these pixels be the same as the left-most image pixels ("replicated border" extrapolation method), or assume that all the non-existing pixels are zeros ("constant border" extrapolation method), and so on. OpenCV enables you to specify the extrapolation method.

Synopsis

Documentation

data MorphShape Source #

Constructors

MorphRect

A rectangular structuring element.

MorphEllipse

An elliptic structuring element, that is, a filled ellipse inscribed into the rectangle Rect(0, 0, esize.width, 0.esize.height).

MorphCross !Point2i

A cross-shaped structuring element.

data MorphOperation Source #

Constructors

MorphOpen

An opening operation: dilate . erode

MorphClose

A closing operation: erode . dilate

MorphGradient

A morphological gradient: dilate - erode

MorphTopHat

"top hat": src - open

MorphBlackHat

"black hat": close - src

laplacian Source #

Arguments

:: ToDepth (Proxy dstDepth) 
=> Maybe Int32

Aperture size used to compute the second-derivative filters. The size must be positive and odd. Default value is 1.

-> Maybe Double

Optional scale factor for the computed Laplacian values. Default value is 1.

-> Maybe Double

Optional delta value that is added to the results. Default value is 0.

-> Maybe BorderMode

Pixel extrapolation method.

-> Mat shape channels srcDepth 
-> CvExcept (Mat shape channels (S dstDepth)) 

Calculates the Laplacian of an image

The function calculates the Laplacian of the source image by adding up the second x and y derivatives calculated using the Sobel operator.

Example:

laplacianImg
    :: forall shape channels depth
     . (Mat shape channels depth ~ Birds_512x341)
    => Mat shape ('S 1) ('S Double)
laplacianImg = exceptError $ do
    imgG <- cvtColor bgr gray birds_512x341
    laplacian Nothing Nothing Nothing Nothing imgG

OpenCV Sphinx doc

medianBlur Source #

Arguments

:: (depth `In` '[Word8, Word16, Float], channels `In` '[1, 3, 4]) 
=> Mat shape (S channels) (S depth)

Input 1-, 3-, or 4-channel image; when ksize is 3 or 5, the image depth should be Word8, Word16, or Float, for larger aperture sizes, it can only be Word8.

-> Int32

Aperture linear size; it must be odd and greater than 1, for example: 3, 5, 7...

-> CvExcept (Mat shape (S channels) (S depth)) 

Blurs an image using the median filter

Example:

medianBlurImg
    :: forall (width    :: Nat)
              (width2   :: Nat)
              (height   :: Nat)
              (channels :: Nat)
              (depth    :: *)
     . ( Mat (ShapeT [height, width]) ('S channels) ('S depth) ~ Birds_512x341
       , width2 ~ ((*) width 2) -- TODO (RvD): HSE parse error with infix type operator
       )
    => Mat (ShapeT [height, width2]) ('S channels) ('S depth)
medianBlurImg = exceptError $
    withMatM (Proxy :: Proxy [height, width2])
             (Proxy :: Proxy channels)
             (Proxy :: Proxy depth)
             white $ \imgM -> do
      birdsBlurred <- pureExcept $ medianBlur birds_512x341 13
      matCopyToM imgM (V2 0 0) birds_512x341 Nothing
      matCopyToM imgM (V2 w 0) birdsBlurred  Nothing
  where
    w = fromInteger $ natVal (Proxy :: Proxy width)

OpenCV Sphinx doc

erode Source #

Arguments

:: (IsPoint2 point2 Int32, depth `In` '[Word8, Word16, Int16, Float, Double]) 
=> Mat shape channels (S depth)

Input image.

-> Maybe (Mat (S '[sh, sw]) (S 1) (S Word8))

Structuring element used for erosion. If emptyMat is used a 3x3 rectangular structuring element is used. Kernel can be created using getStructuringElement.

-> Maybe (point2 Int32)

anchor

-> Int

iterations

-> BorderMode 
-> CvExcept (Mat shape channels (S depth)) 

Erodes an image by using a specific structuring element

Example:

erodeImg
    :: forall (width    :: Nat)
              (width2   :: Nat)
              (height   :: Nat)
              (channels :: Nat)
              (depth    :: *)
     . ( Mat (ShapeT [height, width]) ('S channels) ('S depth) ~ Lambda
       , width2 ~ ((*) width 2) -- TODO (RvD): HSE parse error with infix type operator
       )
    => Mat (ShapeT [height, width2]) ('S channels) ('S depth)
erodeImg = exceptError $
    withMatM (Proxy :: Proxy [height, width2])
             (Proxy :: Proxy channels)
             (Proxy :: Proxy depth)
             white $ \imgM -> do
      erodedLambda <-
        pureExcept $ erode lambda Nothing (Nothing :: Maybe Point2i) 5 BorderReplicate
      matCopyToM imgM (V2 0 0) lambda Nothing
      matCopyToM imgM (V2 w 0) erodedLambda Nothing
  where
    w = fromInteger $ natVal (Proxy :: Proxy width)

OpenCV Sphinx doc

dilate Source #

Arguments

:: (IsPoint2 point2 Int32, depth `In` '[Word8, Word16, Int16, Float, Double]) 
=> Mat shape channels (S depth)

Input image.

-> Maybe (Mat (S '[sh, sw]) (S 1) (S Word8))

Structuring element used for dilation. If emptyMat is used a 3x3 rectangular structuring element is used. Kernel can be created using getStructuringElement.

-> Maybe (point2 Int32)

anchor

-> Int

iterations

-> BorderMode 
-> CvExcept (Mat shape channels (S depth)) 

Dilates an image by using a specific structuring element

Example:

dilateImg
    :: forall (width    :: Nat)
              (width2   :: Nat)
              (height   :: Nat)
              (channels :: Nat)
              (depth    :: *)
     . ( Mat (ShapeT [height, width]) ('S channels) ('S depth) ~ Lambda
       , width2 ~ ((*) width 2) -- TODO (RvD): HSE parse error with infix type operator
       )
    => Mat (ShapeT [height, width2]) ('S channels) ('S depth)
dilateImg = exceptError $
    withMatM (Proxy :: Proxy [height, width2])
             (Proxy :: Proxy channels)
             (Proxy :: Proxy depth)
             white $ \imgM -> do
      dilatedLambda <-
        pureExcept $ dilate lambda Nothing (Nothing :: Maybe Point2i) 3 BorderReplicate
      matCopyToM imgM (V2 0 0) lambda Nothing
      matCopyToM imgM (V2 w 0) dilatedLambda Nothing
  where
    w = fromInteger $ natVal (Proxy :: Proxy width)

OpenCV Sphinx doc

filter2D Source #

Arguments

:: (IsPoint2 point2 Int32, depth `In` '[Word8, Word16, Int16, Float, Double]) 
=> Mat shape channels (S depth)

Input image.

-> Mat (S '[sh, sw]) (S 1) (S Double)

convolution kernel (or rather a correlation kernel), a single-channel floating point matrix; if you want to apply different kernels to different channels, split the image into separate color planes using split and process them individually.

-> Maybe (point2 Int32)

anchor

-> Double

delta

-> BorderMode 
-> CvExcept (Mat shape channels (S depth)) 

Convolves an image with the kernel.

Example:

filter2DImg
    :: forall (width    :: Nat)
              (width2   :: Nat)
              (height   :: Nat)
              (channels :: Nat)
              (depth    :: *)
     . ( Mat (ShapeT [height, width]) ('S channels) ('S depth) ~ Birds_512x341
       , width2 ~ ((*) width 2) -- TODO (RvD): HSE parse error with infix type operator
       )
    => Mat (ShapeT [height, width2]) ('S channels) ('S depth)
filter2DImg = exceptError $
    withMatM (Proxy :: Proxy [height, width2])
             (Proxy :: Proxy channels)
             (Proxy :: Proxy depth)
             white $ \imgM -> do
      filteredBird <-
        pureExcept $ filter2D birds_512x341 kernel (Nothing :: Maybe Point2i) 0 BorderReplicate
      matCopyToM imgM (V2 0 0) birds_512x341 Nothing
      matCopyToM imgM (V2 w 0) filteredBird Nothing
  where
    w = fromInteger $ natVal (Proxy :: Proxy width)
    kernel =
      exceptError $
      withMatM (Proxy :: Proxy [3, 3])
               (Proxy :: Proxy 1)
               (Proxy :: Proxy Double)
               black $ \imgM -> do
        lift $ line imgM (V2 0 0 :: V2 Int32) (V2 0 0 :: V2 Int32) (V4 (-2) (-2) (-2) 1 :: V4 Double) 0 LineType_8 0
        lift $ line imgM (V2 1 0 :: V2 Int32) (V2 0 1 :: V2 Int32) (V4 (-1) (-1) (-1) 1 :: V4 Double) 0 LineType_8 0
        lift $ line imgM (V2 1 1 :: V2 Int32) (V2 1 1 :: V2 Int32) (V4   1    1    1  1 :: V4 Double) 0 LineType_8 0
        lift $ line imgM (V2 1 2 :: V2 Int32) (V2 2 1 :: V2 Int32) (V4   1    1    1  1 :: V4 Double) 0 LineType_8 0
        lift $ line imgM (V2 2 2 :: V2 Int32) (V2 2 2 :: V2 Int32) (V4   2    2    2  1 :: V4 Double) 0 LineType_8 0

OpenCV Sphinx doc

morphologyEx Source #

Arguments

:: (IsPoint2 point2 Int32, depth `In` '[Word8, Word16, Int16, Float, Double]) 
=> Mat shape channels (S depth)

Source image.

-> MorphOperation

Type of a morphological operation.

-> Mat D D D

Structuring element.

-> Maybe (point2 Int32)

Anchor position with the kernel.

-> Int

Number of times erosion and dilation are applied.

-> BorderMode 
-> CvExcept (Mat shape channels (S depth)) 

Performs advanced morphological transformations

OpenCV Sphinx doc

getStructuringElement Source #

Arguments

:: (ToInt32 height, ToInt32 width) 
=> MorphShape 
-> height 
-> width 
-> CvExcept (Mat (ShapeT (height ::: (width ::: Z))) (S 1) (S Word8)) 

Returns a structuring element of the specified size and shape for morphological operations

Example:

type StructureImg = Mat (ShapeT [128, 128]) ('S 1) ('S Word8)

structureImg :: MorphShape -> StructureImg
structureImg shape = exceptError $ do
    mat <- getStructuringElement shape (Proxy :: Proxy 128) (Proxy :: Proxy 128)
    img <- matConvertTo (Just 255) Nothing mat
    bitwiseNot img

morphRectImg :: StructureImg
morphRectImg = structureImg MorphRect

morphEllipseImg :: StructureImg
morphEllipseImg = structureImg MorphEllipse

morphCrossImg :: StructureImg
morphCrossImg = structureImg $ MorphCross $ toPoint (pure (-1) :: V2 Int32)

OpenCV Sphinx doc

blur Source #

Arguments

:: (depth `In` '[Word8, Word16, Int16, Float, Double], IsSize size Int32) 
=> size Int32

Blurring kernel size.

-> Mat shape (S channels) (S depth) 
-> CvExcept (Mat shape (S channels) (S depth)) 

Blurs an image using a box filter.

Example:

boxBlurImg
    :: forall (width    :: Nat)
              (width2   :: Nat)
              (height   :: Nat)
              (channels :: Nat)
              (depth    :: *)
     . ( Mat (ShapeT [height, width]) ('S channels) ('S depth) ~ Birds_512x341
       , width2 ~ ((*) width 2) -- TODO (RvD): HSE parse error with infix type operator
       )
    => Mat (ShapeT [height, width2]) ('S channels) ('S depth)
boxBlurImg = exceptError $
    withMatM (Proxy :: Proxy [height, width2])
             (Proxy :: Proxy channels)
             (Proxy :: Proxy depth)
             white $ \imgM -> do
      birdsBlurred <- pureExcept $ blur (V2 13 13 :: V2 Int32) birds_512x341
      matCopyToM imgM (V2 0 0) birds_512x341 Nothing
      matCopyToM imgM (V2 w 0) birdsBlurred  Nothing
  where
    w = fromInteger $ natVal (Proxy :: Proxy width)

OpenCV Sphinx doc

gaussianBlur Source #

Arguments

:: (depth `In` '[Word8, Word16, Float, Double], IsSize size Int32) 
=> size Int32

Blurring kernel size.

-> Double

sigmaX

-> Double

sigmaY

-> Mat shape (S channels) (S depth) 
-> CvExcept (Mat shape (S channels) (S depth))