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Foundation (CVFoundation.dll) 15.0
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Foundation (CVFoundation.dll) 15.0
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Enumerations | |
| enum | TBlobFeatureType { FBLOB_BLACK_TO_FEATURE = 0 , FBLOB_WHITE_TO_FEATURE = 1 } |
| Feature range to be recognized as an object (blob). More... | |
| enum | TBlobSortDirection { FBLOB_SORT_RISING = 1 , FBLOB_SORT_FALLING = 0 } |
| Sort order of blob objects. More... | |
| enum | TBlobSortMode { FBLOB_SORT_UNSORTED = 0 , FBLOB_SORT_SIZE = 1 , FBLOB_SORT_POSX = 2 , FBLOB_SORT_POSY = 3 , FBLOB_SORT_DISTANCE = 4 } |
| Mode for sorting blob objects. More... | |
| enum | TBlobTouchBorderFilter { FBLOB_BORDER_NONE = 0 , FBLOB_BORDER_RIGHT = 1 , FBLOB_BORDER_TOP = 2 , FBLOB_BORDER_LEFT = 4 , FBLOB_BORDER_BOTTOM = 8 , FBLOB_BORDER_ALL = 15 } |
| Blob object border mask. More... | |
| enum | TCannyEdgeFilter { CE_Scharr = 0 , CE_Sobel = 1 , CE_Sobel2nd = 2 } |
| To apply the Canny Edge detector, the function FilterCanny internally performs a derivative-operation. More... | |
| enum | TDistanceNorm { DN_LInf = 0 , DN_L1 = 1 , DN_L2 = 2 } |
| Indicates the distance norm to be used for the distance transformation (see DistanceTransformation). More... | |
| enum | TFilterMask { FM_3x3 = 0 , FM_5x5 = 1 , FM_7x7 = 2 } |
| Kernel/Mask size. More... | |
| enum | TInterpolationMode { IP_NearestNeighbour = 0 , IP_Linear = 1 , IP_Cubic = 2 , IP_Lanczos = 3 , IP_Supersample = 4 } |
| Mode for sorting blob objects. More... | |
| enum | TMomentsCalculation { MC_FavorNone = 0 , MC_FavorSpeed = 1 , MC_FavorAccuracy = 2 } |
| Specify the preferences for moment calculations. More... | |
| enum | TMorphologyMask { MM_Custom = 0 , MM_Square = 1 , MM_Rect = 2 , MM_Cross = 3 , MM_Circle = 4 , MM_Ellipse = 5 } |
| Defines different types of masks that may be used with the morphological functions ErodeImage, DilateImage, OpeningImage, ClosingImage. More... | |
| enum | TSegmentationBorder { SEGMENTATION_BORDER_NONE = 0 , SEGMENTATION_BORDER_4 = 1 , SEGMENTATION_BORDER_8 = 2 } |
| Specifies the border of the segments. More... | |
| enum | TSegmentationNorm { SEGMENTATION_NORM_INF = 0 , SEGMENTATION_NORM_L1 = 1 } |
| Indicates the norm to form the mask for marker propagation. More... | |
| enum | TThresholdComparison { TH_Less = 0 , TH_LessOrEqual = 1 , TH_Equal = 2 , TH_GreaterOrEqual = 3 , TH_Greater = 4 } |
| Specify the different comparison modes supported by the thresholding functions. More... | |
| enum | TWatershedNorm { WS_NORM_INF = 0 , WS_NORM_L1 = 1 , WS_NORM_L2 = 2 , WS_NORM_FM = 3 } |
| Indicates the norm to form the mask for marker propagation. More... | |
| enum | TWatershedSegmentation { WS_SEGMENT_QUEUE = 0 , WS_SEGMENT_DISTANCE = 1 } |
| Specifies the algorithm how the watershed function is performed. More... | |
| enum | TWaveletFilter { WT_HAAR_FILTER = 0 , WT_DAUB2_FILTER = 1 , WT_DAUB3_FILTER = 2 , WT_DAUB4_FILTER = 3 , WT_BI_1_3 = 4 , WT_BI_1_5 = 5 , WT_CUSTOM = 20 } |
| Wavelet filter to be applied on the input image. More... | |
| enum TBlobFeatureType |
Feature range to be recognized as an object (blob).
| Enumerator | |
|---|---|
| FBLOB_BLACK_TO_FEATURE | The feature is displayed in black. |
| FBLOB_WHITE_TO_FEATURE | The feature is displayed in white. |
| enum TBlobSortDirection |
Sort order of blob objects.
| Enumerator | |
|---|---|
| FBLOB_SORT_RISING | Sorted in ascending order. |
| FBLOB_SORT_FALLING | Sorted in descending order. |
| enum TBlobSortMode |
Mode for sorting blob objects.
| Enumerator | |
|---|---|
| FBLOB_SORT_UNSORTED | Unsorted. |
| FBLOB_SORT_SIZE | Sorted by size. |
| FBLOB_SORT_POSX | Sorted by X-position. |
| FBLOB_SORT_POSY | Sorted by Y-position. |
| FBLOB_SORT_DISTANCE | Sorted by distance to point. |
Blob object border mask.
| enum TCannyEdgeFilter |
To apply the Canny Edge detector, the function FilterCanny internally performs a derivative-operation.
There are three ways currently implemented how FilterCanny may do this:
Scharr, Sobel and 2nd order Sobel
Which of the derivative operators is applied depends on the TCannyEdgeFilter value passed to the function FilterCanny.
| Enumerator | |
|---|---|
| CE_Scharr | Scharr Edge detection operator (see FilterScharrHorizontal and FilterScharrVertical). |
| CE_Sobel | The 1st Order Sobel Filter (see FilterSobelHorizontal and FilterSobelVertical). |
| CE_Sobel2nd | The 2nd Order Sobel Filter (see FilterSobelHorizontal2ndOrder and FilterSobelVertical2ndOrder). |
| enum TDistanceNorm |
Indicates the distance norm to be used for the distance transformation (see DistanceTransformation).
| Enumerator | |
|---|---|
| DN_LInf | Infinity norm. |
| DN_L1 | L1 norm. |
| DN_L2 | L2 norm. |
| enum TFilterMask |
Kernel/Mask size.
The finite impulse response filters implemented in the CVFoundation.dll require that an operation mask is specified either directly or implicitly through the kernel size. There are two ways in which this is done:
Of course it is necessary for the filter functions to access image data beyond the image boundaries. For example a filter function working with a mask of 7x7 pixels, needs to access three pixel coordinates beyond the border of the "real" image data (image e.g. the anchor cell to be located in the top left pixel of the image; only the bottom right corner of the mask covers "real" image data, three quarters are in undefined regions). To resolve this problem, Common Vision Blox always expands the images to be processed by the necessary amount by simply reproducing the image data in the outermost pixel rows and columns.
| Enumerator | |
|---|---|
| FM_3x3 | 3x3 Kernel/Filter mask. |
| FM_5x5 | 5x5 Kernel/Filter mask. |
| FM_7x7 | 7x7 Kernel/Filter mask. |
| enum TInterpolationMode |
Mode for sorting blob objects.
| enum TMomentsCalculation |
Specify the preferences for moment calculations.
| Enumerator | |
|---|---|
| MC_FavorNone | Calculation type (fast or precise) is chosen automatically depending on the image size involved. |
| MC_FavorSpeed | Fast calculation. |
| MC_FavorAccuracy | Precise calculation. |
| enum TMorphologyMask |
Defines different types of masks that may be used with the morphological functions ErodeImage, DilateImage, OpeningImage, ClosingImage.
Depending on the mask type being used, different parameters of those functions will or will not be put to use.
| enum TSegmentationBorder |
Specifies the border of the segments.
All pixel adjacent to the differently marked pixels are considered as border pixels, and their value is set to white (255 in SegmentWatershed and 254 in SegmentGradient).
| enum TSegmentationNorm |
Indicates the norm to form the mask for marker propagation.
This enumeration is used for the function LabelMarker.
| Enumerator | |
|---|---|
| SEGMENTATION_NORM_INF | Infinity norm (8-connectivity). |
| SEGMENTATION_NORM_L1 | L1 norm (4-connectivity). |
| enum TThresholdComparison |
Specify the different comparison modes supported by the thresholding functions.
| enum TWatershedNorm |
Indicates the norm to form the mask for marker propagation.
Specifies the algorithm how the watershed function is performed.
| enum TWaveletFilter |
Wavelet filter to be applied on the input image.
Different standard filters are provided. The provided filters are either orthogonal (Haar, Daubechies 2, Daubechies 3, Daubechies 4) or bi-orthogonal (Bi-orthogonal 1.3, Bi-orthogonal 1.5 filter). The (bi-)orthogonal wavelet transform decomposes the source image into nearly disjoint frequency sub-bands. Using orthogonal wavelet bases the representation of the signal is non-redundant. This means, applying the forward and inverse wavelet transformation on the source images results in perfect reconstruction. All implemented filter coefficients are normalised. Due to perferct reconstruction the values for the reconstruction filters can be computed using the decomposition filter values (high-pass and low-pass filter values).
It is possible to use a different kind of filter. Therefore, specify WT_CUSTOM as input filter. In this case you need to specify the filter coefficients.
