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1
vote
2answers
27 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 ...
0
votes
0answers
13 views

Switching gradient computation in Lucas-Kanade pyramidal feature tracking

The following refers to pyramidal Lucas-Kanade. Given two images $I$ and $J$, we wish to find point $v$ in $J$ which corresponds to point $u$ in $I$. The initial step of the algorithm requires ...
0
votes
0answers
17 views

Excluding the scatter points from a feature

I have a set of data points which are supposed to settle on a locus and follow a pattern, but there are some scatter points in the main locus which their existence in the data can increase the ...
0
votes
2answers
149 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 ...
2
votes
0answers
94 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 ...
1
vote
0answers
63 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 ...
0
votes
0answers
23 views

Fastest implementation of Features from Accelerated Segment Test (FAST) algorithm

I understand that there are different implementations (both in software and hardware) of the FAST algorithm. What is the fastest implementation of Features from Accelerated Segment test (FAST) ...
1
vote
1answer
251 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 ...
0
votes
2answers
158 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 ...
1
vote
0answers
202 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
vote
1answer
55 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
votes
0answers
49 views

CBIR with ORB Feature

I've read the papers (ORB: an efficient alternative to SIFT or SURF), and i believe the step-by-step of ORB to be like this : (1) FAST detector -> (2) Filtered FAST (by Harris) -> (3) Multi-Scale ...
0
votes
1answer
37 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] ...
0
votes
1answer
58 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 ...
0
votes
1answer
73 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 ...
1
vote
1answer
309 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) - ...
0
votes
0answers
125 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 ...
0
votes
0answers
42 views

how to calculate feature points in SIFT?

i wanna know how to calculate key points? im doing it in matlab. when i select 3 DOG(differnce of gaussian) blured image and compared each pixels in the middle image with 26 neighbourhood(including 9 ...
2
votes
1answer
52 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 ...
4
votes
1answer
180 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 ...
4
votes
2answers
107 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 ...
1
vote
2answers
166 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
votes
1answer
125 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 ...
2
votes
1answer
588 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 ...
4
votes
3answers
794 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, ...
0
votes
2answers
1k 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
votes
1answer
2k 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 ...
0
votes
0answers
268 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: ...
2
votes
2answers
159 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) ...
2
votes
1answer
65 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? ...
2
votes
1answer
136 views

Determining false positives in feature matching

I extracted features from an image using SIFT and SURF. Then I applied few transforms on the image and again calculated the features. While matching the features, I noticed that there are some ...
1
vote
1answer
1k views

blob detection using Laplacian of Gaussian filter

I'm learning feature-detectors from this lecture notes, and I don't quite understand the Normalized Laplacian of Gaussian ...
2
votes
0answers
89 views

Affine detector + SIFT descriptor

I am approaching to the Oxford Buildings dataset which contains already computed SIFT descriptors from affine detected keypoint locations. Usually SIFT detector provides to its detected keypoints ...
4
votes
3answers
343 views

Local Image Features Extraction for Road Signs

I'm working on a project to detect a road sign from the Image. Consider the sample image below: I'm using a heuristic search to detect the road sign within an image. Basically, I want some weak ...
5
votes
0answers
67 views

Filtering Corners Detected on Multiple Scales

I made a multi-scale Harris corner detector (inspired by MOPS) which is simply a Harris corner detector performed on several scales (i.e. subsampled versions of the same image). This effectively make ...
2
votes
1answer
720 views

Understanding Integration Scale in Multi-Scale Harris Corner Detector

I would like to improve a simple Harris corner detector by adding more scales. I don't need scale-invariant interest points, just to detect more points by processing more scales. The Wikipedia says ...
0
votes
1answer
219 views

best robust feature detectors for detecting similarities among archeological signs

I would like to implement edge detectors for creating a feature vector for archeological signs. Which are best features, algorithms to retrieve? That could be loaded in a Support vector machine for ...
2
votes
2answers
872 views

A feature extraction method: Principal Component Analysis (PCA)

I read some articles about PCA and I think the nice way to summarize it is: It is a way of identifying patterns in data, and expressing the data in such a way as to highlight their similarities ...
8
votes
3answers
3k views

Scale and Rotation invariant feature descriptors

Can you list some scale and rotational invariant feature descriptors for use in feature detection. The application is for the detection of cars and humans in video captured by a UAV, using a ...
11
votes
2answers
536 views

Image Registration by Segmentation

Image registration algorithms are usually based on point features such as SIFT (Scale-Invariant Feature Transform). I saw some references to line features, but I was wondering if it would be possible ...
3
votes
1answer
120 views

What scale should a detected SIFT point be extracted at?

I've heard this from a few different researchers but I can't find a definitive value. Given the "scale" extracted by David Lowe's SIFT detector, we need to extract a descriptor at a specific scale. ...
7
votes
2answers
368 views

Image Processing Prior to Feature Detection

I have implemented a feature detector based on Harris corners. It works fine most times, but there are cases where it performs poorly. I need to make it work on many different images without ...
9
votes
1answer
1k views

Good features / algorithms for recognizing car-models in images

I have a question concerning object recognition, especially recognizing car-models! I am at the beginning of a work about identifying the same car-model in different images. At the moment I think one ...
5
votes
1answer
341 views

Patent-free Interest Point Detector? [duplicate]

Possible Duplicate: Free alternatives to SIFT/SURF for commercial use There are same very good algorithms for interest point detection/description, like: SIFT (Scale-Invariant Feature ...
5
votes
1answer
281 views

image feature extraction

We are given a set of grayscale image patches obtained from images after edge detection. Each patch is 10x10 pixels with intensity varying between 0 and 255 for each pixel. This set may contain a very ...
11
votes
1answer
784 views

Detection of circles (ellipses) in 2D point cloud

Given a set of points (2D) i.e., point cloud (PC), the question is about a robust, accurate and ...
11
votes
1answer
1k views

Binary robust independent elementary features (“BRIEF”) understanding

How are the descriptors in the BRIEF algorithm matched to each other? How is the template image found in the another image? How do we compare the descriptors? I have read that article but didn't ...
33
votes
3answers
11k views

What are some free alternatives to SIFT/ SURF that can be used in commercial applications?

As far as I understand, both SURF and SIFT are patent protected. Are there any alternative methods that can be used in a commercial application freely? For more info on the patent check out: ...
8
votes
4answers
530 views

Preprocessing to improve Harris corner tracking between video frames?

In our unmanned aerial vehicle grayscale video image stabilization application, we're having difficulty finding the "good" Harris corners in frame N+1 selected from frame N. The source of the ...