9
votes
Best way of segmenting veins in leaves?
Following on from the above excellent answer, here is how to do it in python using scikit funcitons.
...
7
votes
Best way of segmenting veins from arm?
So one good step to enhance the vein-like structures is coherence enhancing diffusion:
Weickert, Joachim. "Coherence-enhancing diffusion filtering." International Journal of Computer Vision 31.2-3 (...
6
votes
What does convolving an image with kernel [1 -2 1] do? How is it different than convolving with the derivative kernel [1 -1]?
Convolution with the [1 -1] kernel (A) is a derivative filter, which computes the finite difference approximation to the first derivative.
The ...
5
votes
Accepted
Detect circles in image
1) Normalize your image to range $[0,255]$.
2) Select a threshold and threshold the image. For your image, what worked is: $\tau=[140-150]$.
3) Compute a Euclidean distance transform.
4) Apply ...
4
votes
Accepted
Deriving the Euler-Lagrange Equations for the Chan-Vese Model
Thanks to Luminita Vese, who responded to this question via email. I will post the answer here. Let $\varphi_\epsilon(x) = \varphi(x) + \epsilon\eta(x)$ for some test function $\eta(x)$.
\begin{...
4
votes
Accepted
What Is the Difference Between MRF and Total Variation in Noise Removal?
These are two different concepts that you talk about. First, MRF gives you a framework to do discrete optimization of problems, which respect the Markovian property, that is a pixel is conditioned ...
4
votes
Accepted
What does convolving an image with kernel [1 -2 1] do? How is it different than convolving with the derivative kernel [1 -1]?
Both are high pass filters. Filtering with [1 -2 1] is the same as filtering with [1 -1] twice. So the longer kernel is a steeper high pass filter and emphasize the edges more.
4
votes
Accepted
Can DFT magnitude be used to identify repeating patterns in an Image?
Yes, the DFT magnitude can reveal repetition patterns in an image. I provide an intuitive understanding for the results returned by the DFT which will hopefully make the interpretation of the DFT ...
3
votes
Gap Filling Contours / Lines
I managed to find a solution of your problem by simply using a disk-like structuring element instead of a square/rectangular one for the closing operation. A comparison of both approaches' results is ...
3
votes
How to Use Maximum a Posteriori Probability (MAP) in Classification Task
I will try to give you some intuition into it by a different example.
Think we have 3 machines which can generate the numbers 1, 2, 3.
The first machine generates the number 1 with 80% and the ...
3
votes
Accepted
How to prove $\int_{\Omega} \sum_{i=1}^{N} f_i(x)dx$ is equivilant with $\sum_{i=1}^{N} \int_{\Omega} f_i(x)u_i(x)dx$
Starting from your $E_2$ and exchanging the finite sum with the integral we get this:
$$E_2=\sum_{i=1}^N \int_\Omega f_i(x) u_i(x) dx = \int_\Omega \sum_{i=1}^N f_i(x) u_i(x) dx$$
Next we can use ...
3
votes
Accepted
How to quantify area of interest in an image?
Given that the size of the barnacles is not expected to be considerably larger than the area of the hull being imaged at a certain shot, you can simply deduce the actual barnacle coverage area by ...
3
votes
Best way of segmenting veins in leaves?
This topic has always attracted a lot of interest, and yet no real consensus exists on the topic. Therefore I decided to drop a few words.
My answers to previously asked similar questions on ...
3
votes
Vein extraction from this image
I would like to direct you to 3 references:
C. Steger: “Extracting Curvilinear Structures: A Differential
Geometric Approach”. In B. Buxton, R. Cipolla, eds., “Fourth European
Conference on ...
3
votes
How does image masking work?
You may interpret it this way, but this yields a limited interpretation, because for instance the image may have a maximum different from $255$.
I consider masking as a product operation. For a ...
3
votes
Accepted
Histogram of Gradient
For the sake of putting some numbers to this question, I implemented a basic histogram of gradient from scikit-image (skimage.feature.hog). Here is the timing data ...
3
votes
Accepted
Finding minimum in the middle of a histogram
To me, this looks like you want something like
start from right. Add up bins' values, as long as
the added bin is larger than the last or
the value added by that bin divided by the current sum is ...
3
votes
Lighting for computer vision automisation
What I learned so far that my lighting is not good. It's coming from a fluorescent lamp from that's right above the camera. Apparently I would have to diffuse the light with some sort of material. The ...
3
votes
Accepted
Fitting a grid to points in a 2d space
You could represent the grid with 5 parameters:
(x0, y0) to represent the offset from your image origin to the grid
origin
(xs, ys) to represent a multiplication factor from your image
plane to your ...
3
votes
Accepted
Should Edge Detection Be Applied in Spatial or in Frequency Domain?
We need to separate the concept of edge detection from the tools we use to apply the procedure.
Edges are local property of the image. Being so local means we don't analyze the image in frequency ...
3
votes
Any good alternatives of ImageJ (Fiji)?
If you’re looking for a large collection of image processing functionality geared towards quantification, I will recommend DIPlib (I’m an author). It is different from ImageJ in that it doesn’t have a ...
2
votes
Accepted
Convergence criteria for Active contour model
You could set a pre-defined maximum number of iterations. Moreover, you could limit the minimum update of the level-set. That is, the total evolution at a given time-step should exceed a threshold $\...
2
votes
Segmentation of small artifacts - Image Processing
If this is really what your input looks like then you should be able to handle this with the standard morphological image processing operations.
Assuming foreground as white and background as black, ...
2
votes
Accepted
Connecting segmented region in image
I guess that the missing area is due to a ring. A solution would be to use a PCA in order to compute the finger orientation. Then you apply a closing (mathematica morphology) with an segment oriented ...
2
votes
Accepted
Comparison between watershed and grabcut
Watershed-based segmentation will typically lead to over-segmentation, and is very sensitive to local image noise (e.g. see discussion here). Typically watersheds are pruned/merged by using thresholds ...
2
votes
Scikit-Image, Numpy, and Selecting Colors (python)
You can look at your picture in a different color space, e.g. the HSV space. In this space, each pixel has 3 components: hue, saturation and value. Hue defines the color's tone, saturation the color's ...
2
votes
Accepted
Scikit-Image, Numpy, and Selecting Colors (python)
Thanks to Maximilian Matthé, I have an answer. Below is his OpenCV code translated to Scikit-image. Note that I changed some parameters (e.g., reduce the size of the morphological disk) to replicate ...
2
votes
Detect almost circular shapes in RGB image
The image itself is somehow blurred a little. Whole edges of trees are not visible. The only clue of tree existence seems like shadows. So I suggest using shadow information and watershed transform ...
2
votes
Simple technique to segment out optical disk and vessels from retinography
I managed to get a decent segmentation of the optical disk and vessels by applying some basic operations to the input image, starting with loading and grayscaling it:
...
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