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15 votes
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What Is the Difference between Difference of Gaussian, Laplace of Gaussian, and Mexican Hat Wavelet?

Laplace of Gaussian The Laplace of Gaussian (LoG) of image $f$ can be written as $$ \nabla^2 (f * g) = f * \nabla^2 g $$ with $g$ the Gaussian kernel and $*$ the convolution. That is, the Laplace ...
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10 votes

In opecv function Hough circles how does parameter 1 and 2 affect circle detection and how can I adjust them to increase accuracy?

Intuition for parameters of HoughCircles: image: 8-bit, single channel image. If working with a color image, convert to grayscale first. method: Defines the method to detect circles in images. ...
9 votes

How do I get the most accurate camera calibration?

I decided to post this answer here because a while back, this came up as the top result in Google and its suggestions helped me. So I decided to share my experience too. Having spent countless hours ...
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8 votes
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How to remove the noise without destroying the main edge?

Use bilateral filter or anisotropic diffusion first. The effect of anisotropic diffusion is as the following: . The MATLAB code can be found here. Here is its effect on your image: Finally, non-...
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8 votes
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How to Get Rid of Ripples from a Gradient Image of a Smoothed Image?

I think it happens due to 2 things: Quantization You are working using UINT8 Image, try convert it into floating Point Image. You may do this by ...
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7 votes
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Isolate the non blurred part of foucsed image

In general, this is an image segmentation problem (http://en.wikipedia.org/wiki/Image_segmentation) into which you would be trying to isolate the focused to the non-focused regions of the image. ...
  • 10.4k
7 votes

How do I get the most accurate camera calibration?

Here is a list of 'best practices' for camera calibration which I originally posted here: https://calib.io/blogs/knowledge-base/calibration-best-practices Choose the right size calibration target. ...
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7 votes
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K-means for 2D point clustering in python

It can be done very easily with the scikit-learn. Examples are easy to find on their website, i.e. here. In my opinion it is the best way to go. Modified code example from the above link: ...
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7 votes
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Gaussian Equivalent of Convolving an Image 50 Times with a Box Filter

What you should do is work with the Variance. The Variance of Discrete Random Variables with support of $ \left[ -l, l \right] $ is given by (Notice that since the Expected Value is $ 0 $, the ...
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6 votes
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Is it possible to hack camera calibration without having access to the camera?

If I understand correctly, you don't need the intrinsics or extrinsics to achieve that, if a top-down view is all you want. You could basically define 4 points on your parallel lines and then warp the ...
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6 votes
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In opecv function Hough circles how does parameter 1 and 2 affect circle detection and how can I adjust them to increase accuracy?

If you have an idea what size circles you are looking for, then it would be best to set min_radius and max_radius accordingly. Otherwise, it will return anything circular of any size. Parameters 1 ...
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6 votes
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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 ...
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6 votes

What Is the Best Color Space to Work with for Hand Detection: RGB, HSV, or YCrCb?

Intuitively, HSV is the place to easily define Skin Color Hues. Yet there is a broad work on that and even articles about the optimal Color Space for Skin Detection. Yet, you should have a look at ...
  • 48k
6 votes

Image Gradient: Light to Dark, Dark to Light

The UINT8 type is limited to integer numbers on the range [0, 1, 2, ..., 255]. Hence negative values are clipped into 0. A solution could be wither use other types (Floating Points) or scale and ...
  • 48k
6 votes
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Python - Normalized cross-correlation to measure similarites in 2 images

I guess you can compute for each pixel the correlation coefficient between patches centered on this pixel in the two images of interest. Here is an example where I downloaded the figure attached here ...
6 votes

What Is the Difference between Difference of Gaussian, Laplace of Gaussian, and Mexican Hat Wavelet?

The Ricker wavelet, the (isotropic) Marr wavelet, the Mexican hat or the Laplacian of Gaussians belong to be the same concept: continuous admissible wavelets (satisfying certain conditions). ...
6 votes
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Given a set of lines, find only those who are parallel (perspective)

Parallel lines in the image do intersect at a vanishing point. Therefore simply hypothesizing lines (a gradient direction at a point suffices to describe it) and voting (see Hough voting) would ...
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6 votes
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Redistributing Color in a RGB Image According to a Gaussian Distribution

After you equalize the histogram you can think of your data as a stream of variables $ {X}_{i} $ where $ X \sim U \left[ 0, 1 \right] $. Now all you need is to transform samples of Uniform Random ...
  • 48k
6 votes

Recommended Order of Performing Denoising, Deblurring and Super Resolution on an Image

If your image is modeled as an image which is noisy, blurry and heavily decimated the optimal thing to do is estimate the image given that model. The model is well defined in @Laurent Duval's ...
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6 votes
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How to Remove Double Lines Detected Along the Edges by Edge Detector?

I ran the following code: ...
  • 48k
5 votes

Noise Removal from an Image Using OpenCV (Comparison to Neat Image)

NeatImage probably uses Wavelets based Noise Reduction. You can look for methods based on that. Today you need methods which are "Edge Aware", namely they smooth yet keep edges in tact. Have ...
  • 48k
5 votes

Isolate the non blurred part of foucsed image

Here is an easier approach, that does not involve sliding-window analysis. Convert your image to grayscale (this is not required, but I will assume that you only have one channel for the sake of ...
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5 votes
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Getting Composition of a Mixture of Colors

You actually have 3 independent equations. If one of them is solvable, all three are. Now, the equation is given by: $$ z = \alpha x + \left( 1 - \alpha \right) y $$ Assume $ \alpha, x, z $ are ...
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5 votes
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How to Find the Probability of Kalman Filter States?

The idea of Kalman is it fuses the data with the optimal weighing to get results. Optimal requires definition and in the case of Kalman it means that if your model is right this is the optimal. Since ...
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4 votes

Finding the Harmonics contained in an Image?

this questions is asked fairly often. If you don't have a grasp of fft in 1d, higher dimensions may be difficult to grasph. But logically it makes a lot of sense once you see it What does frequency ...
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4 votes
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Computing cross-correlation of two images using OpenCV

On closer inspection, I discovered that the erroneous correlation result resembles the correct result, but shifted up and to the left. The former was displayed in scientific format, so it was hard to ...
  • 501
4 votes

What Is the Difference between Difference of Gaussian, Laplace of Gaussian, and Mexican Hat Wavelet?

Let's see how DoG approximates LoG for the 2D case (for an image, e.g.). By derivative theorem of convolution (by associativity and commutativity), $$\nabla^2[f(x, y) \ast G(x, y)] = \nabla^2 G(x, y) \...
4 votes

Removing noisy lines from image - opencv - python

first of all remember that there is no single solution for all kind of noise and all kind of images. that being said i can think of two solution. first is using Otsu thresholding: ...
4 votes

Outlined text extraction from image using OpenCV

You can obtain pretty good results by just thresholding the image at a high intensity (since your text appears always to be white) and do a closing operation to close the gaps: ...
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4 votes

Finding Homography Matrix Using Lines

I am not aware of any library which works directly on lines. A by pass would be, that given 2 line, you'd use a finites sample of point on the lines to calculate the Homography. To derive the ...
  • 48k

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