Operator Library: Logic
The IF operator checks if a condition input is true and forwards the corresponding values of the data input. The operator is equipped with a parameterizable number of input links I0..In-1. With each input link comes a conditional input Condition. If a condition is true, the data of its corresponding input is forwarded to the output. If all condition inputs are false, the Else input is used. If more than one condition input is true, all corresponding input links are forwarded to the output and combined using a logic OR operation. The operator can be used with kernels. Each kernel component is selected independently.
Property | Value |
---|---|
Operator Type | O |
Input Links | I0, data input I1..In-1, data input Else, data input Condition0..n-1, data input |
Output Link | O, data output |
The use of operator IF is shown in the following examples:
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'Combine Image Data From Two Camera Sources - Building an Overlay Blend'
Tutorial - From equation to implementation. Explanation on how to implement the overlay blend.
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Examples - A convolution with high intensity spot coefficients is made. For results above threshold, the respective pixels are dyed in red.
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Examples - A high speed and robust laser line detection algorithm. The algorithm determines center of gravity coordinates to obtain sub-pixel resolution results.
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Examples - Shows the usage of operator Blob_Analysis_1D in line scan applications.
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'Nearest Neighbor Demosaicing'
Examples - Nearest Neighbor Bayer Demosaicing
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'Edge Sensitive Bayer Demosaicing Algorithm'
Examples - Edge Sensitive Laplace Bayer Demosaicing filter
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'Bayer Demosaicing Algorithm According to Laroche'
Examples - Laroche Bayer Demosaicing filter
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'Modified Laroche Bayer Demosaicing Algorithm '
Examples - Ressource Optimized Laroche Bayer Demosaicing filter
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Examples - Color Classification is very simple on HSL images. The applet converts the RGB image into an HSL image and performs a color classification. The hue is filtered using a lookup table. Moreover, the saturation and lightness is thresholded using custom threshold values.
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'High Dynamic Range and Low Dynamic Range Example Using Camera Response Function'
Examples - High Dynamic Range According to Debevec
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'High Dynamic Range and Low Dynamic Range Example with a Weighted Linear Ansatz'
Examples - High Dynamic Range with Linear Ansatz
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'Depth From Focus Using Loops'
Examples - Depth From Focus using Loops
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Examples - The examples shows an automatic dead pixel detection and replacement.
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Examples - A grid is overlayed to the input images. The grid pixel value is determined from the input pixel value.