18
votes
Accepted
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 ...
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 ...
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. ...
6
votes
Accepted
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
Accepted
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 ...
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 ...
5
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
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
You might be able to take these steps:
Use Otsu threshold cv2.threshold(img, 0, 255, cv2.THRESH_BINARY_INV|cv2.THRESH_OTSU) to get the image in only pure white ...
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:
...
4
votes
Detecting bullet holes using Python with camera or sensors
I can't really comment on the machine vision part, other than any question that asks "How do I do <some signal processing task> in <some language>" is fairly naive. The way you ...
4
votes
Which Blur is being used in this effect
So I tried what has been suggested on this image
Here's the python code :
...
4
votes
Accepted
Can DFT magnitude be used to identify repeating patterns in an Image?
Yes, the DFT magnitude can reveal repetition patterns in an image. I provide an intuitive understanding for the results returned by the DFT which will hopefully make the interpretation of the DFT ...
3
votes
Gap Filling Contours / Lines
I managed to find a solution of your problem by simply using a disk-like structuring element instead of a square/rectangular one for the closing operation. A comparison of both approaches' results is ...
3
votes
Measuring the contrast of an image
A simple way to calculate contrast is by computing the standard deviation of the greyed image pixel intensities.
3
votes
Vein extraction from this image
I would like to direct you to 3 references:
C. Steger: “Extracting Curvilinear Structures: A Differential
Geometric Approach”. In B. Buxton, R. Cipolla, eds., “Fourth European
Conference on ...
3
votes
Accepted
NORM_HAMMING2 vs NORM_HAMMING
From BFMatcher constructor documentation:
NORM_HAMMING should be used with ORB, BRISK and BRIEF, ...
3
votes
Accepted
How can I construct a Band-pass filter from a low and a high-pass filter?
Yes you are correct. You apply them if series in they are linear.
One simple band-pass filter you could use is called the difference of Gaussian (DoG)
The procedure is:
Create a Gaussian filter ...
3
votes
Accepted
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 ...
3
votes
Accepted
How can I isolate a Hough circle that I perceive to be the best fit, but is ranked much lower?
The Hough Transform is "right". Because it searches for the most consistent "shape" given the accumulated values. If all you would like to do is to find the center of the spot, there are other ...
3
votes
Image Shadow Removal Using OpenCV and Python
fgbg = cv2.createBackgroundSubtractorMOG2(128,cv2.THRESH_BINARY,1)
masked_image = fgbg.apply(image)
in masked_image shadow will be grey color(pixel value= 127)
...
3
votes
Accepted
How to detach overlapping contours but not to remove small ones. Alternative to erosion-dilation cycle
I don't know if this is a corner case or the norm in your dataset but it is a relatively easy situation to deal with. It would be much more difficult to detect trees in an urban environment, for ...
3
votes
Accepted
Licence plate enhancement
I guess image denoising and image super-resolution techniques could be used to enhance license plate images.
Here are a few relevant links:
Image denoising based - SNIDER: Single Noisy Image ...
3
votes
Salt and Pepper impulse Denoising opencv
Can we consider these noises as salt and pepper noise.? Is there something else that I am missing?
several pixels getting erased to either zero or one -> yeah, that fits my definition of salt and ...
3
votes
What happens when you read and save the same JPEG image again over and over?
JPEG is lossy compression, and it is allowed to do anything deemed beneficial in representing an image as accurately as possible using the minimum amount of storage while keeping cpu load in check. ...
3
votes
Removing white reflective pixels from scanned RGB image (Python - preferably OpenCV)
This is the best I could come to. Improvements are extremely welcome.
...
2
votes
DFT and Inverse DFT in Image Processing
I saw same issue, and I found the answer in stackoverflow - DFT to spatial domain in OpenCV is not working.
for short, you can set imaginary part of filtering kernel zeros before you call mulSpectrums....
2
votes
How to make color balance of photoshop using opencv
OpenCV don't have any apis to separate data into lowlight,midtones and highlights.But you can categorize pixels in image into shadows,mid-tones and highlights by setting some thresholds.As they depend ...
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