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Questions tagged [feature-extraction]

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Speech Endpoints Detection using Explicit approach

The "Fundamentals of Speech Recognition" text by Rabiner, mentions three approaches for Speech (Endpoints) detection - Explicit, Implicit, and Hybrid approaches. I am studying the block ...
Anantha Krishnan's user avatar
1 vote
1 answer
72 views

How to feed multi-channel spectrograms to Deep Neural Network?

I am using a 14 channel EEG device. To do away with the need for any handcrafted features, I wish to implement an ML classification task with the EEG data collected using deep neural networks (such as ...
Anantha Krishnan's user avatar
1 vote
0 answers
106 views

Does ORB-Slam3 perform better than ORB-Slam2?

I was trying to compare ORB-Slam2 performace with ORB-Slam3 performance. Consider following comparison from ORB-Slam3 paper (columns with numbers correspond to different sequences from EuRoC dataset): ...
Mahesha999's user avatar
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0 answers
15 views

How orientation is used in FAST features in ORB?

I was going throught ORB paper. It states that it adds an efficiently computed orientation to FAST features. The description explains how it calculates Moment of patch $$m_{pq}=\sum_{x,y}x^py^pI(x,y)$...
Mahesha999's user avatar
1 vote
0 answers
66 views

Which filter is suitable for reducing noise in feature detection?

I have a feature detection algorithm that is called FAST - Feature Accelerated Segmented Test. It's a very fast algorithm for finding feature points, e.g "corners" inside an image. Here is ...
euraad's user avatar
  • 405
1 vote
0 answers
50 views

MFCCs are useful for speech & music analysis. For music, why isn't the 12-tone scale used instead of the mel scale?

As far as I understand, the mel scale was developed empirically using something akin to "just noticeable differences" in a subject's perception of frequencies. The scale ends up being a log ...
sguis's user avatar
  • 11
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0 answers
35 views

Isn't the MFCC feature good for real time applications?

I am interested in the audio classification problem. You can think of the problem as ML, but my question is from a signal processing perspective. I am questioning the classification performance of ...
Yalçın Cenik's user avatar
0 votes
0 answers
6 views

Feature for a signal classification

Consider that i have N signals of electricity energy consumption (from N different consumers) that ha 24 measurements over a ...
Murilo's user avatar
  • 113
2 votes
1 answer
176 views

How to extract the oscillation frequency from the following signals?

Signals contain both transient and stabilizing processes. In the transient process, the signal exhibits oscillatory behavior with damping. Is there some efficient algorithms to extract the frequency? ...
Always_young_1's user avatar
1 vote
0 answers
170 views

Is lock-in amplifier a correct approach?

I have a noisy signal which is the voltage output from a photodetector circuit. I have researched about extracting signals, and found that lock-in amplifiers are one of the main approaches for the ...
Teena's user avatar
  • 21
1 vote
1 answer
288 views

Lock-in Amplifier: How to improve the output of lock in amplifier?

I tried to extract a pure signal from the noisy signal using a lock-in amplifier with the help of python code. The output is from a photodetector circuit. These are the reference signal, expected ...
Teena's user avatar
  • 21
2 votes
1 answer
99 views

How to simplify several cross correlations used for feature extraction

I have a system where I cross correlate recorded audio signals with several smaller generated signals to extract feature vectors that later I use in a kNN matching. The system works the way I want it ...
besabestin's user avatar
2 votes
1 answer
51 views

Can the FFT be employed to make a dataset as Multivariate Normal distributed?

I have dataset composed of a large number of images with a large size (i.e., 32x32px), and I'm trying to adapt a feature extraction framework which assumes that the input dataset is Multivariate ...
Francesco Binucci's user avatar
2 votes
2 answers
209 views

Anonymize / Obfuscate speech when doing audio classification

Let me preface that I am new to audio processing and audio analysis ;) (I asked the same question on reddit, I wanted to increase it's reach)) I am trying to classify specific events (like a gong or ...
Hurricane's user avatar
0 votes
1 answer
103 views

STFT Audio processing with zeros

In this paper they preprocess an audio file with a STFT and then apply two equations to the computed matrix. I tried implementing all of it in python and used librosa for the STFT. The issue I ...
Rocket's user avatar
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0 answers
74 views

FFT of frequency bands and limited amplitude modulation

In this paper they preprocess a cent spectrum of an audio file. For comparison of audio files they create the Logarithmic Fluctuation Pattern(LFP)(p.3). For this I have to use a FFT on each frequency ...
Rocket's user avatar
  • 25
3 votes
3 answers
252 views

Resource recommendations to learn audio processing

I'm looking for some good resources to learn audio processing for a machine learning task based on classification of users as either 'COVID-19 positive' or 'COVID-19 negative' based on their cough ...
Anonymous's user avatar
3 votes
1 answer
366 views

Short time energy or root mean square?

What is the difference between Short time energy(STE) or root mean square(RMS), Librosa library offers a function to calculate RMS but doesn't offer one to calculate STE, which gives the impression ...
Ahmad's user avatar
  • 33
3 votes
1 answer
147 views

The SIFT Descriptor and Image Resolution

When reading about SIFT I read halving resolution is the same as increasing $\sigma$ of the gaussian in terms of feature detection but reducing resolution has the advantage of reducing processing. ...
FourierFlux's user avatar
1 vote
1 answer
61 views

preparing the ct scan data of a patient, using a visible feature in the mri image

A dataset of mri and ct scan images of patients has been prepared. There is a feature /damaged area/ in the mri image that is easily visible. But the injury of this area is not visible in the CT scan ...
Erfan Pot's user avatar
2 votes
2 answers
121 views

Extract diagonal area from image

I have a gray scale image of fibres in different orientations. My goal is to mark the area where the fibres have a specific angle and neglect the rest. In the future it should be an automated process ...
Till's user avatar
  • 131
6 votes
1 answer
710 views

Why is scaling of images / pixels into `[0, 1]` range performed before SIFT (Scale Invariant Feature Transform) algorithm?

The SIFT paper and the paper of Anatomy of the SIFT Method do not mention that the input images should be preprocessed (normalized, re-scaled) before feeding images into the standard SIFT algorithm. ...
Lion Lai's user avatar
  • 213
2 votes
1 answer
1k views

Log Mel Spectrogram vs Log Mel Power Spectrogram

I'm doing some feature extraction on audio signals. $M$ being a mel filterbank matrix, and $S$ being the spectrogram (extracted from the Short Time Fourier Transform of my audio signal), we can ...
Jdip's user avatar
  • 6,265
0 votes
1 answer
128 views

Power Spectrum for feature extraction

I want to extract frequency domain features for my machine learning model, and to do so I have calculated the power spectrum of the EMG signal. One of my first questions is that my frequency is just ...
ADSS's user avatar
  • 3
0 votes
0 answers
53 views

Adjust Wavelet output to CNN

I want to extract features from the signal using DWT and then feed the results into CNN, after calling the 'dwt' library function I got a runtime error. ...
yba's user avatar
  • 11
0 votes
0 answers
263 views

How to get epochs from eeg data in python?

I am working on sleep stage classification and have EEG data from the link : https://physionet.org/content/hmc-sleep-staging/1.1/ I am using pyedflib to extract the data. I am tring to extract the ...
FredyJames21's user avatar
1 vote
1 answer
940 views

Should i normalize FFT signal with z-score?

I am working with EEG data (time domain) in a machine learning task, where each input signal must be mapped to a class/frequency. I am using FFT in order to get data in frequency domain and make ...
heresthebuzz's user avatar
1 vote
1 answer
199 views

SURF normalisation and Haar wavelet

I am reading the SURF paper (Speeded-Up Robust Features (SURF)) but can't understand two things. In 3.2 it says: Furthermore, the filter responses are normalised with respect to their size. This ...
sucicf1's user avatar
  • 113
0 votes
1 answer
670 views

Extracting "frequency domain features" from signal for classification

I have a real signal with only nonnegative values (actigraph measurements). Many papers say they use "frequency domain features" for classification, such as mean, variance etc. But I'm ...
qalis's user avatar
  • 111
4 votes
2 answers
318 views

Accurate phase calculation in sinusoidal linear regression?

I've been trying to work out a way to minimize the error in phase calculation. The underlying model is the following $$s(t) = \sum_{i=1}^{M} A_i\sin\left(\frac{2\pi t}{T_i} + \phi_i\right) + \...
Cifer's user avatar
  • 41
2 votes
1 answer
4k views

Understanding GCC-PHAT as a Feature

I'm working on a sound source localization project and am interested in using GCC-PHAT as a feature. I'm quite new to this transformation and I've been reading a few papers about it and I'm still ...
user25758's user avatar
1 vote
1 answer
165 views

What are features in signal processing using a more tangible or less abstract description

I'm learning about signal processing for music, and in my reading I keep finding the term "features". I find that they never really give a concrete example of what they mean by "...
Sam's user avatar
  • 111
1 vote
0 answers
93 views

Logarithmic Amplitude Spectral Subtraction

I'm diving into audio processing and I'm trying to wrap my head around spectral subtraction. I learned there are different approaches do it based on power, magnitude, oversubtraction. My task is to ...
lima0's user avatar
  • 9
1 vote
0 answers
27 views

Feature extraction for IRIS recognition

What are types for feature extraction in iris recognition? How can I divide it on types which detect phase, edge, etc.?
Olo's user avatar
  • 73
1 vote
0 answers
33 views

feature extraction techniques for iris recognition

I want to ask how I can divide feature extraction techniques to feature detectors and feature descriptors. I have big problem how to understand it. For example I can use Gabor filters (feature ...
Olo's user avatar
  • 73
0 votes
0 answers
110 views

DWT and FFT on a very low frequency signals

I am trying to extract features from a very low frequency signal of $0.1$ HZ and less than $100$ samples. Is it advisable to use FFT and DWT on this signal?
aven's user avatar
  • 1
1 vote
1 answer
189 views

Invariances of FFT-based Image-Registration vs. SIFT-Features

TL;DR: I don't understand how invariant FFT-based image-registration techniques are to object alterations (scratches, marks etc.) in comparison to SIFT-features. I want to build kind of a feature-...
Tim Hilt's user avatar
  • 201
1 vote
0 answers
91 views

ORB Implementation, Scale Pyramid, rFAST

Reading this ("ORB: An efficient alternative to SIFT or SURF") paper, I am not certain how they use the scale pyramid. It says it is created and FAST feature detectors are employed at every ...
Darian Dzirko's user avatar
1 vote
1 answer
210 views

How can I better extract the hidden images in FEZ's soundtrack?

I believe I have found a (new?) secret in FEZ's soundtrack, but my visualizer isn't clear enough to capture it 100%. In FEZ's soundtrack (by Disasterpeace), there are "secrets"- stuff like ...
user avatar
0 votes
2 answers
137 views

Working with a sound's magnitude instead of amplitude

I'm working on a project, where we're recording sound with a piezo-disc which looks a little something like this: Now, unless we're doing something horribly horribly wrong, I've discovered that we're ...
madprogramer's user avatar
1 vote
1 answer
272 views

What is the purpose of dividing an audio signal into segments and analysis each segment?

I read bunch of materials for extracting feature from audio signal and they all tell me to break signal into segments, why don't we analyze all the audio signal? I don't know what are the advantages ...
Mrnobody's user avatar
0 votes
0 answers
59 views

How can I stitch bottom of some image to topside of another image by erasing as much overlapped image as possible?

I have 2 images of size 1920*1080 and I want to try image-stitching on them. These are images (images are from wind turbine blade.) This is the first image And the second image. I already have ...
masouduut94's user avatar
3 votes
2 answers
1k views

Why do we need multiple layers in each octave and multiple octaves in SIFT?

I skimmed through the SIFT paper. I understand that there are multiple octaves, which are composed of multiple layers. The layer $k$ of an octave (btw, where does this name come from?) corresponds to ...
user avatar
0 votes
1 answer
158 views

KLT for an ECG Signal

I am currently searching for methods of feature extraction from an ECG signal and I've stumbled upon the Karhunen–Loeve Transform. I've read some papers and I think I get the basics but my question ...
Ali Co.'s user avatar
0 votes
0 answers
191 views

Feature extraction for exponentially damped signals

I am looking into exponentially damped signals where it is a stationary signal (after implementing the Adfuller statistical test) and I would like to look into how can I extract meaningful features ...
Lenman147's user avatar
1 vote
1 answer
388 views

Understanding the Threshold Process in Harris Corner and Edge Detector

I have read the paper Chris Harris , Mike Stephens - A Combined Corner and Edge Detector about the Harris Corner and Edge Detector, but I didn't understand the point that after low and high threshold ...
Bilal's user avatar
  • 167
1 vote
2 answers
667 views

log base in log-power spectral features

Is the log in log-power spectral features natural logarithm, or common log of base 10? does it even matter? I found sources for how to calculate it, but they all call it 'log'. no one mentions the ...
Xgk's user avatar
  • 13
1 vote
1 answer
50 views

What is the HOMING operator?

I was reading "Optical Recognition Systems" book and in chapter 3.3.2.3 where methods for full genetic programming are described, a paper is describing an ADF (automatically defined functions) like ...
KababChi's user avatar
0 votes
1 answer
88 views

which features fundamental frequency is correlated?

I'm unable to compute $f_0$ (fundamental frequency) in librosa feature extraction. By ready much in github issues check the second comment. I see that $f_0$ is ...
abdoulsn's user avatar
  • 119
-1 votes
2 answers
615 views

how to extract a radio signal features with python?

I have a dataset of radio signals that i want to classify. So, I decided to extract features. After some googling, I have noticed that I have to calculate moments, cumulants, Kutosis and skewness to ...
nechi's user avatar
  • 1