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Owning Palette: Feature Extraction VIs
Requires: Advanced Signal Processing Toolkit
Uses the multiresolution wavelet analysis to extract the edges of a signal.
|signal specifies the 2D input signal.|
|threshold ratio specifies the relative threshold to use to reject small peaks. threshold ratio is defined in the range [0, 1], where 0 and 1 correspond to the minimum and maximum values of the coefficients, respectively. The smaller the value of threshold ratio, the more edges this VI detects.|
|levels specifies the number of levels in the discrete wavelet analysis. levels must be a positive integer no greater than log2(Ls), where Ls is the length of the 1D signal or the minimum dimensional size of the 2D signal. Otherwise, you can set the value to –1, which indicates that this VI sets levels as the largest integer no greater than log2(Ls). The default is –1.|
|error in describes error conditions that occur before this node runs. This input provides standard error in functionality.|
|edges returns the detected edges at different levels. The ith element of edges contains the edges of signal at the (i+1)th level. The edges at smaller levels reveal the details of the image, and the edges at larger levels provide the global and large-scale edges of the image, for example, the contour of an image. |
|error out contains error information. This output provides standard error out functionality.|
Usually, the modulus-maxima of the detail coefficients of signal corresponds to the edge of signal. This VI completes the following steps to implement the multi-scale edge detection.
Refer to A Wavelet Tour of Signal Processing for more information about multi-scale edge detection.
Refer to the Image Edge Detection VI in the labview\examples\Wavelet Analysis\WAApplications directory for an example of using the WA Multiscale Edge Detection VI.