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5 votes

discrete definitions of curl $\nabla \times F$?

Continuous It looks like you only need 2d curl, so let's start with a simpler continuous definition: $$ \omega = \nabla \times \mathbf{u} = \frac{\delta v}{\delta x} - \frac{\delta u}{\delta y} $$ ...
hyperpallium's user avatar
5 votes
Accepted

Iterative camera calibration - No convergence

I have to tell you. I implemented this algorithm (even double checked with other experienced people), however no luck. I guess, this worked for the authors, but with our data there was really no ...
Tolga Birdal's user avatar
  • 2,239
4 votes
Accepted

Which image filter acts like "surface tension"?

Morphological Closing. A morphological closing is a combination of dilation followed by erosion; typical image processing operations available in most image processing libraries. SciPy has a "...
André's user avatar
  • 207
4 votes

Shape measure for C-shaped objects

How about something like radial integral channel features? Affordable person detection in omnidirectional cameras using radial integral channel features, Barış Evrim Demiröz, Albert Ali Salah, Yalin ...
Tolga Birdal's user avatar
  • 2,239
4 votes

Eigenvalue decomposition for a very huge matrix of medical images (such as the pixel physical coordinates of CT images)

Take a look at the literature that does similar things for facial recognition -- search for the term "eigenface", for example. The point to make in this context is that the information you ...
Wolfgang Bangerth's user avatar
3 votes
Accepted

Compute point-spread-function between original and blurred image

We construct an operator based on the assumption that the system is a linear space invariant system. The blurred image is denoted $b$ and the input is denoted $x$. Since the convolution is commutative,...
Ron's user avatar
  • 725
3 votes
Accepted

Evaluate 3D Shape Descriptor

3D local feature descriptors for shapes are very well studied. Typically, people tend to represent the input as a set of points (point clouds) and try to characterize the local neighborhoods with ...
Tolga Birdal's user avatar
  • 2,239
2 votes

Fitting rectangle to segments in image

You might be able to do better than simple gradient descent using an algorithm like BFGS, which uses the history of the gradients as well as the approximate solutions to try and approximate the ...
Daniel Shapero's user avatar
2 votes

discrete definitions of curl $\nabla \times F$?

This is made a lot easier by introducing the Calculus of Finite Differences. If $u_{i,j}$ is grid function defined for integer $i,j$ then the y-differencing operator $$\delta_y u=u_{j+1}-u_j$$ is ...
Philip Roe's user avatar
  • 1,154
2 votes

Automatic motion recognition

You would greatly benefit from knowledge in signal processing, but some specific useful knowledge would be in computer vision and estimation (like Kalman filters or alpha beta filters). With respect ...
spektr's user avatar
  • 4,258
2 votes
Accepted

What is a good algorithm, and framework, to calculate centres of gravity or mass (cog)?

There are several alternatives: Alternative #1: you need to find for each cell of the tessellation the list of pixels contained in the cell. To do that, you can use a rasterization algorithm. You can ...
BrunoLevy's user avatar
  • 2,315
2 votes

Is the inverse radon transform considered a linear operation?

For an operator $R$ to be linear, it has to satisfy two conditions: $R(f+g) = Rf + Rg$ for any two operands $f,g$; $R(\alpha f) = \alpha Rf$ for any operand $f$ and (real or complex) number $\alpha$. ...
Wolfgang Bangerth's user avatar
2 votes

Which technique to use for signal/image processing or noise removal?

You may start with median or Gaussian filters. There are many libraries that implement them and they are simple to use. That said, I think this approach may be not enough because from what I've seen ...
KjMag's user avatar
  • 121
2 votes

Which image filter acts like "surface tension"?

I think that you could use a Gaussian Filter. The following Python code does something similar to what you show in your images. ...
nicoguaro's user avatar
  • 8,534
2 votes

Algorithm to determine flat surfaces and camera orientation without specialized hardware

You are quite right, Augmented Reality benefits a lot from a combination of video/image analysis together with the data from motion sensors. Quote from Apple ARKit: Understanding World Tracking: To ...
Anton Menshov's user avatar
  • 8,692
2 votes

Is there an efficient algorithm for matching objects in one image to objects in another?

I guess what you are referring to is the cross-correlation between the images. This is very good and efficient to find shifts, but not changes in scale and orientation. As you probably know, the cross-...
doetoe's user avatar
  • 593
2 votes

Is there an efficient algorithm for matching objects in one image to objects in another?

Disclaimer: This is most likely not the most efficient, promising way to go about it. When I was looking up the same topic from a similar interest (Analyzing microscopy images), I came across the ...
BmyGuest's user avatar
  • 121
2 votes
Accepted

Polygon approximation with a circle

They just curve fit the two equations $$ x(\omega) = h - b \sin(\omega) ~,~~ y(\omega) = k + a \cos(\omega) $$ using a nonlinear curve fitting algorithm. However, the accuracy of the fit depends ...
Biswajit Banerjee's user avatar
2 votes

Eigenvalue decomposition for a very huge matrix of medical images (such as the pixel physical coordinates of CT images)

Let us proceed systematically: numerical precision of data (you said from medical imaging) number of operations required for standard methods (as from libraries) possible out-of-core computation (i.e....
Stef's user avatar
  • 21
2 votes

How applying the gradient descent method for solving a least square problem can remove the blur from an image?

The problem is equivalent to: $$ \arg \min_{\boldsymbol{u}} \frac{1}{2} {\left\| \boldsymbol{G} \boldsymbol{u} - \boldsymbol{f} \right\|}_{2}^{2} $$ The solution is given by $ \hat{\boldsymbol{u}} = {\...
Royi's user avatar
  • 332
2 votes
Accepted

First derivatives in Python Image Processing?

A gradient is not immediately well defined for digital images because they are both: Quantized (the image values have a finite number of possible values E.g. 0-255 or likewise) The image is ...
Dith's user avatar
  • 98
2 votes
Accepted

Calculating camera calibration matrix with Scilab

I found the answer. The videos I was looking at didn't mention a very important detail. The QR factorization needs to be applied to the inverse of the first three columns of P. The resulting K is also ...
Vaahterasiirappi's user avatar
1 vote

How can I compute the gradient of the noiseless image given by the compass operator?

Lets say you want to calculate the gradient in the horizontal direction for one cell right next to the central area of increased grey value (I marked the pixel in grey), Then you multiply the values ...
MPIchael's user avatar
  • 2,985
1 vote

Is it possible to resample grid in such a way so that continuous objects remain continuous?

I think the problem is that you've lost the topology upon the first rasterization: | 0 | 1 | 1 | 0.5 | 0 | could be ...
iliar's user avatar
  • 253
1 vote

Poisson image blending artifacts

It seems I forgot to accumulate the boundary terms for each relevant entry in the right hand side vector $b$. So ...
ShnitzelKiller's user avatar
1 vote

Image hash similarity matching possible?

Assuming you are talking about a cryptographic hash (as opposed to a hash used for speeding lookups, say), I think you are posing contradictory requirements. The purpose of a hash is to remove any ...
SolverWorld's user avatar
1 vote

Methods to implement floor dirt detection algorithm

Here are some suggestions: Whatever method you try, look at a large number of dirty floor samples to get an idea of the range of things - is it a darker area, is it streaks, etc. For a simple idea, ...
SolverWorld's user avatar
1 vote
Accepted

Filter coefficients for convolutional inpainting

This is basically a computation of stencil coefficients for a finite difference method. Expand each cell value in terms of the center using Taylor series. Note that $\Delta_{x} = \Delta_{y} = \Delta$ ...
gpavanb's user avatar
  • 572
1 vote

Finding intersections of curves in a binary image

You can also have a look at detecting crossing with the local Hessian matrix : https://dsp.stackexchange.com/questions/10579/how-hessian-feature-detector-works It can detect "corners" (intersection of ...
ZiGaelle's user avatar
  • 121

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