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13 views

How can I use Hermite Kernel as feature extraction?

I'd read about hermite polynomials, hermite filter and hermite kernel which is I'm not sure if all of these are the same thing. I can't understand how these thing can be used in image processing. Is ...
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1answer
44 views

Feature matching of images without corners

I am trying to stitch aerial images using feature-based registration. Most image pairs are matched well, such as this: Others are not matched due to lack of common features: As you can see, the ...
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2answers
58 views

Useful natural “Hilbert-like” $n$-uples and $n$-fold "analytic signals

If $\mathcal{H}$ denotes the Hilbert transform, the analytic signal of a signal $x(t)$ is $$x_a(t) = x(t) +\imath \mathcal{H}(x(t))\,.$$ The real and imaginary parts form Hilbert pairs. Are there ...
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0answers
25 views

Feature Descriptor for Hough Transform

I'm trying to implement rotation/scale invariant Generalized Hough Transform (i.e. template-matching algorithm). The main problem of this approach is computational complexity (it requires at least 4-...
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1answer
46 views

Determinant of Hessian approximation (SURF)

I have a question regarding formula in SURF article by Bay et al. Theory Given a point $p=(x,y)$ in an image $I$, the Hessian matrix $\mathcal{H}$ in $x$ at scale $\sigma$ is defined as follows $$ \...
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0answers
21 views

Get level of wellness in a cascade classifier using LBP

I'm currently working in a Lolipop LBP cascade detector using OpenCV. The training is correctly done and the cascade classifier detects the sticks of the Lolipops correctly but with some minor errors. ...
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0answers
67 views

How to match a thumbnail to an area in the original image?

Suppose that you have a thumbnail and the original image from which it was generated. You need to match the thumbnail to an area in the original image that represents the original selection from which ...
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2answers
128 views

Should I use CV_HAAR_SCALE_IMAGE while using LBP CascadeClassifier?

I trained a cascade-LBP to detect Lollipops with 1000 images, now I'm trying to "adapt" the openCV HAAR-Cascade example to use my LBP trained .xml but I'm not sure about the "HAAR_SCALE_IMAGE" flag, I ...
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1answer
121 views

Structure Tensor vs. Hessian Matrix

Hello can someone explain the semantical meaning of the structure tensor and the Hessian matrix. I am aware of how it is calculated, but i find it difficult to comprehend what they describe in the ...
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0answers
110 views

Determinant of Hessian blob response

this question is about blob detection based on the determinant of Hessian as i am working with the SURF method. In the method SURF (speeded up robust features) by Bay et al. a local 3x3x3 ...
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2answers
46 views

What makes a feature stable?

Feature detection is an essential task in low-level vision. Good features are those that resist to different perturbations such as noise addition, blur, geometric transforms (3D rotation with ...
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0answers
7 views

Harris / Plessy Anisotropic response

Harris and Stephens states that they avoid the problem of anisotropic response: "all possible small shifts can be covered by performing an analytic expansion about the shift origin": Where the image ...
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1answer
36 views

Moravec, Harris noisy window

Harris and Stephens writes about the interest window of Moravec: "The response is noisy because the window is binary and rectangular", and suggests applying a Gaussian window. My Question: Why is the ...
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0answers
70 views

Question about SURF - speeded up robust features

I am trying to get my head around the SURF detection method (fast hessian), but I have run into some problems. I have only just begun to look at it, so I apologize for any "ill" asked questions. I am ...
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2answers
107 views

texture matching between patches of an image

I have an image A which I have divided into 4 x 4 subband images. For a given patch P1 in ...
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0answers
10 views

Redundant basis instead of PCA

I have an matrix of $M$ feature vectors with $N$ observations. Using PCA I can get an $N \times N$ orthonormal basis where each vector corresponds to the features of maximal variance. Is there an ...
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0answers
116 views

What's the optimal filter size for a 2D Gabor filter

I started to experiment with Gabor filters to extract various image features from usual camera snapshots (that's the image domain: everyday snapshots with a very diverse range of subjects). ...
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4answers
157 views

What kind of features can I extract from this signal

I want to monitor (automatic-)gearbox failures on some vehicles. For each vehicle I have a captured signal representing the selected gear at each one millisecond. An example of two signals are shown ...
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1answer
814 views

difference between feature detector and descriptor?

I am new to feature detection and tracking. can anybody please explain in detail the difference between detector and descriptors. which among these are detectors and which are descriptors : Harris, ...
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0answers
82 views

pre-processing to improve feature detector before tracking

I am trying to make tracking for soccer player, I need to detect features from this player and then estimate the distance difference of these pixels over number of frames. first I have to detect the ...
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0answers
20 views

what is in intuitive explanation of local derivative pattern (LDP)?

Zhang et al. proposed the LDPs for face recognition . They considered the LBP as the nondirectional first-order local pattern operator and extended it to higher orders ( th-order) called the LDP. is ...
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1answer
108 views

Haralick features, am I approaching this correcly?

I'm trying to personalise a custom CBIR by adding more features not only based on colour, but based on textures' features. What I don't know is if I'm approaching this well with Haralick's features. ...
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0answers
172 views

Efficient Hessian-Laplace blob detector implementation

As it is mentioned in a paper for SURF, it is possible to approximate hessian determinant using integral images. If I want to implement Hessian-Laplace detector, is it feasible to also approximate ...
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3answers
133 views

Need critical help: How to detect and distinguish two very similar looking signals?

Hi guys I have a really tough signal processing question here. How do you detect and distinguish two very very similar looking waves? I need to distinguish between these two signals for an online ...
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1answer
405 views

Suggested Preprocessing methods for OCR on Circular Images

Hello this is my sample image I am going to do real time character detection on images like that. I've tried SURF, SIFT, MSER and template matching on original image without any preprocessing. I can ...
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2answers
58 views

LoG filter creating additional maxima in scale space

To create a scale space, I applied a Laplacian of Gaussian filter on the following image: After the scale space was created, I plotted circles around local maxima in scale space. However, instead ...
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2answers
2k views

Finding local brightness maximas with OpenCV

I want to find points (of a processed image) that are the brightest in their local region. Basically, I want all of the points whose 8 neighbors are all smaller but I want to have brighter maxima ...
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0answers
701 views

Why is LBP generaly faster than HAAR?

I am digging into Haar like and LBP features. More precisely its implementation in OpenCV. Every article or forum entry I found states, that LBP is faster than Haar. My local tests also confirm this ...
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0answers
299 views

Visual regression test - Extract elements of GUI-Screenshot - MSER OpenCV

For a visual regression test I need to compare screenshots of webpages (different release-versions). I started with pixel by pixel compare. Actually I split the screenshot in different parts (maybe ...
2
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1answer
2k views

Zernike Moments' implementation in OpenCV

The reason why Hu moments were implemented in OpenCV and why Zernike moments were not implemented is looking like their performance similar as stated in this paper. As stated in the paper Zernike ...
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2answers
169 views

Detecting sound inside a sound

I was searching on the Internet hopelessly about some materials regarding detecting a sound in another sound. Say, I've got a recorded short sound (which may be anything, fragment of speech, fragment ...
2
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0answers
686 views

MPEG-7 descriptors' implementation in OpenCV

I'm looking for implementation of MPEG-7 descriptors which are compatible with OpenCV's recent versions and containing "region-based shape descriptor ART(Angular Radial Transformation)". I ...
1
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1answer
106 views

Can SIFT run in realtime?

What is the best possible runtime for extracting SIFT keypoints and Descriptors? I know it depends on #keypoints extracted. So, say for image of size 640x640, the code that I have been using requires ...
0
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1answer
57 views

need general resource about image matching

i'm working on image matching mainly SIFT and SURF for my thesis. i read Moravec's and harris corner detectors and understand them quiet well in my own opinion.A COMBINED CORNER AND EDGE DETECTOR[1] ...
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1answer
153 views

Phase reference of a periodic signal

Assume an arbitrary (discrete) signal that is periodic and known over a whole period. I need a way to select a characteristic point along the signal such that I can always retrieve it even when the ...
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1answer
147 views

Feature for exact matching of images

I am trying to match images from a large dataset which exactly match the given input image.(images with deformations/transformations are treated as different) I have tried euclidean distance but it ...
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1answer
1k views

Feature extraction/reduction using DWT

For a given time series which is n timestamps in length, we can take Discrete Wavelet Transform (using 'Haar' wavelets), then we get (for an example, in Python) - ...
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0answers
395 views

CWT for filtering / feature extraction

I had asked a question last night in regards to how to process my data (Noise rejection / feature extraction) but I have a more specific question now that I hope someone can answer. As mentioned in ...
2
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1answer
72 views

What is localizability in Computer Vision?

Please consider the following excerpt (from Rodrigo R, Zouqi M, Chen Z, Samarabandu J.: Robust and efficient feature tracking for indoor navigation): Robust feature tracking is a requirement for ...
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1answer
405 views

Corner detection using Chris Harris & Mike Stephens [duplicate]

I am not able to understand the formula, What is $W$ (window) and intensity in the formula mean, I found this formula in opencv doc http://docs.opencv.org/trunk/doc/py_tutorials/py_feature2d/...
4
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2answers
128 views

mean of wavelet for image processing

For many papers which talks about using wavelet transforms for feature detection in image processing, it is stated that it is advantageous for the wavelet to have zero mean? Why is this so? Thanks in ...
2
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2answers
658 views

Methods to quantify randomness (or complexity) in a signal

What are the methods through which we can quantify the randomness or complexity in a given signal. I know spectral flatness measure (geometric to arithmetic means) is one way to do it, but what are ...
3
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1answer
301 views

proving that a log gabor filter has 0 DC offset

I have read somewhere online that the log gabor filter has an advantage over the gabor filter, in the sense that it has 0 DC component. How do you prove this property mathematically? Thanks in advance....
3
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1answer
2k views

difference between Gabor and log-Gabor function

I am reading a paper using log-gabor filters for feature detection. I was thinking about the difference between Gabor filters and log-gabor filters. Can anyone tell me the difference(s), and a way to ...
5
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3answers
1k views

Purpose of image feature detection and matching

I'm a new guy in image processing and computer vision, so this question might be stupid to you. I just learned some feature detection and description algorithms, such as Harris, Hessian, SIFT, SURF, ...
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2answers
3k views

normalized Laplacian of Gaussian

Laplacian of Gaussian formula for 2d case is $$\operatorname{LoG}(x,y) = \frac{1}{\pi\sigma^4}\left(\frac{x^2+y^2}{2\sigma^2} - 1\right)e^{-\frac{x^2+y^2}{2\sigma^2}},$$ in scale-space related ...
5
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1answer
6k views

How Hessian feature detector works?

I know about Harris corner detector, and I understand the basic idea of its second moment matrix, $$M = \left[ \begin{array}{cc} I_x^2 & I_xI_y \\ I_xI_y & I_y^2 \end{array} \right]$$, edges ...
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0answers
615 views

HOG descriptor algorithm

I would like to implement a HOG descriptor in C++. I found an implementation of this code here. An extract of the code follows: ...
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3answers
271 views

What are integration scale and differentiation scale?

In scale-adapted Harris detector, the scale adapted second moment matrix is defined by: $$\mu(x, \sigma_I, \sigma_D) = \sigma_D^2\ g(\sigma_I) *\left[ \begin{array}{cc} L_x^2(x, \sigma_D) &L_xL_y(...
2
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1answer
81 views

feature detectors and descriptors comparison

There are several kinds of detectors and descriptors, like SIFT, SURF, FAST. I wonder are they all eligible for real-time applications? Which is the best or better? ...