Objects			page : 1 2 3 4
242.eclipse03	External		meta-imaging with threshhold inversion
242.thresh	External		makes darker regions black
2threshattack~	External		Two-threshold 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 top-leftmost 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 1-plane long matrix. There is a hard-coded 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 ID-tagged 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 over-threshold for wait time. bangs when values are over-threshold for wait time.
DPXThreshEmitter.mxo	External		External
page : 1 2 3 4