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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. ...
Matthew Shun-Shin's user avatar
6 votes

How to decide whether a recording contains a signal of interest?

Is it possible to decide based on the result of the cross-correlation whether a recording contains the signal of interest? Certainly. The easiest way would be look at the crest factor (peak to RMS ...
Hilmar's user avatar
  • 45.3k
6 votes

Detect valleys of a signal

First, you'll probably have better luck posting this on dsp.stackexchange. That's a more specialized group that does stuff like this all the time. In terms of your problem, here's a couple of ...
Daniel K's user avatar
  • 309
6 votes

What are the most common algorithms for adaptive thresholding?

This question has been answered very well from different perspectives, and I just want to summarize my experience and also emphasize some problems related to adaptive binarization. Adaptive ...
feelfree's user avatar
  • 497
3 votes

Optimal Level of Wavelet Decomposition for Denoising

Best denoising should be related to certain quality measures, often requiring the clean signal reference, which you do not have in general. Or you could rely on some reference-free measures. To the ...
Laurent Duval's user avatar
3 votes
Accepted

In Plain English, What Are the Within and Between Class Variances in Otsu's Thresholding?

i'm avoiding labels light and dark because you could say that we choose 128 as threshold which perfectly separate light and dark pixels but consider you have a picture with only two gray levels which ...
Mohammad M's user avatar
  • 1,327
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 ...
Tolga Birdal's user avatar
  • 5,465
2 votes

Double Threshold Mechanism

It is possible that it refers to hysteresis thresholding. This is where the image is thresholded twice, at a low threshold and a high one. The connected components of the low threshold that contain at ...
Cris Luengo's user avatar
  • 2,584
2 votes

Threshold for peak detection of noisy signal in frequency domain

This is a pretty common problem in radar signal processing. Typically, we’ll use what’s called a CFAR detector (constant false alarm rate). This essentially boils down to a non-linear smoothing filter ...
vintagevogue's user avatar
2 votes

How to decide whether a recording contains a signal of interest?

Have you tried setting a threshold based on the signal statistics? For your first approach (could be applied to your second as well, only in the frequency domain), that would look something like: <...
Jdip's user avatar
  • 6,265
2 votes
Accepted

Finding optimal decision threshold for binary comm system

Let P(0) ( P(1) ) is a probability of transmitting bit zero (one); P(e|0) ( P(e|1) ) is a probability of error when detecting bit zero (one). The probability of erroneous detection is $$ P(e) = P(e|0)...
V.V.T's user avatar
  • 1,739
1 vote
Accepted

Concept of energy threshold

Does the "Energy Threshold" carry information about the end of the noise and the beginning of the packet due to the calculated arithmetic mean? There's no such thing as "end of noise&...
Marcus Müller's user avatar
1 vote

What are the possible ways to find spots with most concentrated contrast on an image?

Pass a sliding window of eg 100x100 pixels over the image stepped 1 pixel at a time in each dimension. Note the maximum and the minimum pixel value. The local contrast is now the local_max/local_min. ...
Knut Inge's user avatar
  • 3,434
1 vote

How to determine a suitable threshold when using amplitude thresholding method for spike detection?

For threshold-based spike detection, the threshold defines your performance in the detection vs false alarm performance. That is to say, a lower threshold will improve your probability of detecting (...
Florian's user avatar
  • 2,463
1 vote

Signal analysis: selection of oscillatory parts

Take a morlet wavelet and run it over the entire signal. The frequency in the morlet wavelet can be set close to the frequency of these transitory regions. Even if not close to frequency of transition ...
Dsp guy sam's user avatar
  • 2,620
1 vote
Accepted

Signal analysis: selection of oscillatory parts

By looking at that graph, it seems that simple math (or rather statistics) can be used to solve this problem. I'd divide (segment) your data into equal time frames and then compute the mean and ...
dsp_user's user avatar
  • 921
1 vote

Good way for segmenting this signal

I solved this by still using Otsu to find the threshold value. I then just filter the the regions with value == 1 in the thresholded signal (i.e. the ...
packoman's user avatar
  • 255
1 vote

How to discard deviating values from standard deviation and running average

Let's ignore the issue that you already have a discrimination problem in your hands (bus/car/truck/van) there is an initial discrimination problem that has to be solved for the data to be considered ...
Edgar Brown's user avatar
1 vote

Threshold for peak detection of noisy signal in frequency domain

Look for peaks N dB above the localized noise floor. Calculate the noise floor by taking the mean of all your samples (or choose an observation window size). You can throw out the top 1-3 samples (...
BigBrownBear00's user avatar
1 vote

Detect valleys of a signal

I did not read carefully through the whole question as I don't have time now, but have you tried some form of robust peak detection? See e.g., https://docs.scipy.org/doc/scipy/reference/generated/...
Effesian's user avatar
1 vote

Binarization, and then thinning/skeletonization

Your implementation of the ZS algorithm is wrong. The correct output should be: Here you can see the output superimposed on the original binary image: Removing the small branches would require a ...
Costantino Grana's user avatar
1 vote

Is document image binarization a closed research field

First, in science, a field is rarely closed, sometimes asleep only. Resistance to low-contrast, real-time, badly scanned, composite documents/writers or from aging medium seem to remain challenges, ...
Laurent Duval's user avatar
1 vote

select local maxima in energy signal

I would suggest you apply a median filter, e.g., y=filter(1,0.05*ones(1,20),x) And then apply Matlab function findpeaks. As an ...
Filipe Pinto's user avatar
1 vote

Optimal Level of Wavelet Decomposition for Denoising

I'd say it depends on the noise properties and of course the image itself. What you can think is that most Denoise Filters can handle only the High Frequencies of the noise. Hence the decomposition ...
Royi's user avatar
  • 19.7k
1 vote

Motion detection one threshold over dataset

I could suggest several things. I am not sure if you already try them and I am not sure of the requirements either. Assuming that you need real-time analysis and performances: What about normalizing ...
Arritmic's user avatar
  • 301
1 vote
Accepted

What Is the Cause for Poor Results with Adaptive Thresholding?

Some guidelines for using Thresholding: Stretch the image to use the whole Dynamic Range (DR). Apply some Denoising (Very very gentle). Median with small radius would be a good idea. Unless you hand ...
Royi's user avatar
  • 19.7k
1 vote

Diagonal vs non diagonal processing for audio denoising

I find the diagonal term a bit confusing. Sometimes, for wavelets, people separate scalar and vector or block thresholding. [EDIT] Now I believe I understand it. If you put all your samples or ...
Laurent Duval's user avatar
1 vote

What are the various techniques for detecting walls in buildings (architectural) in floor plan images?

Try using Template matching by taking a small cutout of the wall whose length is long enough so that it is not confused with other elements. Keep the threshold value high(around 0.9 or higher) and ...
Swastik's user avatar
  • 11
1 vote

Denoising by DCT and hard thresholding

DCTs are very useful at energy compaction, so simply put after a DCT of an image is resolved to a weighted some of some basis functions. After a DCT, the resulting matrix will contains multipliers for ...
hit.at.ro's user avatar
  • 111

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