curve

I have taken out the laser curve of this image : (source: hostingpics.net ) And now, I'm trying to obtain a set of points (the more, the better), which are in the middle of this curve. I have tried to split the image into vertical stripes, and then to detect the centroid. But it doesn't calculate lots of points, and it's not satisfactory at all ! img = cv2.Canny(img,50,150,apertureSize = 3) sub = 100 step=int(img.shape[1]/sub) centroid=[] for i in range(sub): x0= i*step x1=(i+1)*step-1 temp = img[:,x0:x1] hierarchy,contours,_ = cv2.findContours(temp, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

This question already has answers here : Closed 8 years ago . Possible Duplicate: Akima interpolation of an array of doubles I'm searching for an algorithm for Akima interpolation, but I can't find one after googling for a while. I write my application in Objective-C, but the programming language doesn't matter. It would be very kind if you can provide any code or links. Thanks Handcraftsman edit: see this SO answer for an updated version of the list below. original answer: Akima's original paper http://student.ndhu.edu.tw/~u9111023/akima.pdf C# implementation https://github.com/mathnet

I have the image of an open curve in a numpy array and I need to build a list of points coordinates ordered according to their position on the curve. I wrote a draft script using numpy and mahotas. It may not be optimal. I know that OpenCV can do this for a closed curve. Can OpenCV do the same (faster) with an open curve? For example, if the original curve is: [[0 0 0 0 0 0 0] [0 1 0 0 1 0 0] [0 0 1 0 0 1 0] [0 0 0 1 1 0 0] [0 0 0 0 0 0 0]] Using np.where(myarray==1) , I can get the indices of the pixels: (array([1, 1, 2, 2, 3, 3]), array([1, 4, 2, 5, 3, 4])) But this not what I need. My

In my 2D game I'm using graphic tools to create nice, smooth terrain represented by black color: Simple algorithm written in java looks for black color every 15 pixels, creating following set of lines (gray): As you can see, there's some places that are mapped very bad, some are pretty good. In other case it would be not necessary to sample every 15 pixels, eg. if terrain is flat. What's the best way to covert this curve to set of points [lines], using as little points as possible? Sampling every 15 pixels = 55 FPS, 10 pixels = 40 FPS Following algorithm is doing that job, sampling from right