gaussian

Is there a way to apply a Gaussianblur or median smoothing filter to a mat of floating points while supplying a mask of pixels that should be ignored? could you please help me? ty. You can do this by: Zeroing out the regions outside the mask Smooth the image and the mask Divide each pixel in the smoothed image with the value of the smoothed mask The division in step 3 compensates for the black pixels introduced by masking. This works because the smoothed mask is darkened in the same way as the smoothed masked image. Yeah, so i figured it out. I had to define my own gaussian smoothing procedure

I am reading Elements of Statistical Learning ESLII and in chapter 2, they have a gaussian mixture data set to illustrate some learning algorithms. To generate this data set, they first generate 10 means from a bivariate gaussian distribution N((1,0)', I). I am not sure what they mean? How can you generate 10 means from a bivariate distribution having mean(1,0)? Each of the means that are generated from the bivariate Gaussian distribution are simply single points sampled in exactly the same way as any other random points that could be generated from the distribution. The fact that they use

This question already has an answer here : Closed 7 years ago . Possible Duplicate: Generating a random Gaussian double in Objective-C/C Is there any way of getting a random number not from a uniform distribution, but from a Gaussian (Normal, Bell Curve) distribution in iOS? All the random number generators I have found are basically uniform and I want to make the numbers cluster around a certain point. Thanks! Just use a uniform distribution generator and apply the Box-Muller Transform : double u1 = (double)arc4random() / UINT32_MAX; // uniform distribution double u2 = (double)arc4random() /

I try to learn and implement a simple genetic algorithm library for my project. At this time, evolution, selection of population is ready, and I'm trying to implement a simple good mutation operator like the Gaussian mutation operator (GMO) for my genetic evolution engine in Java and Scala. I find some information on Gaussian mutation operator (GMO) into the paper A mutation operator based on a Pareto ranking for multi-objective evolutionary algorithms (P.M. Mateo, I. Alberto), page 6 and 7. But I have some problem to find other information on how to implement this Gaussian mutation operator

In a project I'm working on I need to obtain a Gaussian fit from a set of points - needing mean and variance for some processing, and possibly an error degree (or accuracy level) to let me figure out if the set of points really have a normal distribution. I've found this question but it is limited to 3 points only - whereas I need a fit that can work with any number of points. What I need is similar to the labview Gaussian Peak Fit I have looked at mathdotnet and aforge.net (using both in the same project), but I haven't found anything. Does anybody know any C# or (easily convertible) C/C++ or

I have a moving background image and I want to blur the bottom part of it out. I would do it with just photoshop but since the image moves, it wouldn't work very well. Here is what I mean (look at the bottom of the image) : So basically like the effect the dock has on the iPhone. I'm using iOS 8 but not Swift. I have done a small example based on the photo you have there. My algorithm is as follows: Extract a portion of image from bottom. Apply gaussian filter to it and blur it. Then, create a new image context, draw original image on it. Then, draw the blurred portion of the image to place it