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242.eclipse03
 External 

metaimaging with threshhold inversion 
242.thresh
 External 

makes darker regions black 
2threshattack~
 External 

Twothreshold attack detector, aka a Schmitt Trigger http://en.wikipedia.org/wiki/Schmitt_trigger 
bthresher~
 External 

bthresher~ extends the thresher model, to give independent control over the parameters of each individual bin. bthresher~ extends the thresher model, to give independent control over the parameters of each individual bin. You can also randomly set damping and threshold values, and can dump the current values (to possibly send as input to another bthresher~ unit). 1 comment 
burrow~
 External 

filtering burrow~ performs filtering much like drown~, but it utilizes a second signal input to utilize as a filter threshold reference. The threshold controls the extent of the filtering. It is specified in dB. Useful values lie in the range from 0 to 90 dB. Threshold inversion is available via the invert message. 
cv.jit.label
 External 

This algorithm scans through the image and gives each connected component an individual value. This algorithm scans through the image and gives each connected component an individual value. If you set the "mode" attribute to its default value of 0, it will paint the topleftmost blob with ones, and will number blobs incrementally moving right and down. In mode 1, however, it will paint the blobs with the number of pixels in that blob. This can allow you, for instance, to filter only blobs that have sizes between such and such a value. Furthermore, in either mode, you can use the "threshold" attribute to erase all the blobs that are smaller than the threshold value. This is an extremely powerful (and surprisingly cheap) way of filtering noise out. In order to accommodate potentially large numbers of blobs, or large blob sizes, the output is a 1plane long matrix. There is a hardcoded limit of 2048 possible blobs. 
cv.jit.stddev
 External 

Computes the standard deviation of the incoming matrices. Computes the standard deviation of the incoming matrices. The standard deviation is simply the square root of the variance, so the same result can be obtained with cv.jit.variance and a jit.op object. The standard deviation is a measure of how much sample values vary from the mean, or in other words, how wide the distribution on either side of the mean is. About 65% of sample values fall within one standard deviation of the mean, whereas 95% are within twice that value. This measurement is very useful when it comes to setting bounds or threshold values, for instance in a background subtraction operation. If the mean value of a background pixel is 50, and the standard deviation is 10, then a pixel valued at 80 would be considered foreground. However, if the standard deviation is around 30, there is a good chance that it belongs to the background. 
cv.jit.threshold
 External 

Adaptive thresholding. Uneven illumination is often a problem when thresholding an image. Adaptive thresholding addresses this issue by adjusting the threshold based on the brightness of an area surrounding each pixel. 
dot.attackslope
 Abstraction 

Given two thresholds, determine the slope between the points at which they are crossed in the positive direction (i.e., attack speed). 
dot.channelthresh
 Abstraction 

Combines IDtagged channels into lists using a delay threshold. Like “thresh,” but keeps channel information. 
dot.split
 Abstraction 

Right outlet if greater then threshold, left outlet otherwise. Right outlet if greater then threshold, left outlet otherwise. 
dot.thresh
 Abstraction 

A little hack to allow thresh to work with symbols. 
dot.threshtrig
 Abstraction 

Output a value only once after passing the threshold in the positive or negative directions. 
dot.wait
 Abstraction 

bangs when values are overthreshold for wait time. bangs when values are overthreshold for wait time. 
DPXThreshEmitter.mxo
 External 

External 
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