# Tag Info

Accepted

### Why Is the Canny Edge Detection Used Instead of Sobel / Prewitt Edge Detection Before Hough Transformation?

Canny Edge Detection is considered to be a better (In False Alarm sense) edge detection than those you mentioned. This is, mainly, due to 2 steps: Non Maximum Suppression - Edges candidates which are ...
Accepted

### How to calculate particles sizes for spheric particles with overlapping and superposition? (Example image included)

Here is what I experimented with: Use ELSD to generate elliptic contours. You could basically use any edge detector, but since in the following stages I will benefit from circle detectors, it is good ...

### 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. ...

### Why Is the Canny Edge Detection Used Instead of Sobel / Prewitt Edge Detection Before Hough Transformation?

Your statement that the Hough transform (HT) needs to be applied on a binary image is not true. The original HT indeed was formulated that way, though in the meanwhile different authors extended the ...
Accepted

### 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 ...
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 ...
Accepted

### Detect circles in image

1) Normalize your image to range $[0,255]$. 2) Select a threshold and threshold the image. For your image, what worked is: $\tau=[140-150]$. 3) Compute a Euclidean distance transform. 4) Apply ...
Accepted

### Fitting a grid to points in a 2d space

You could represent the grid with 5 parameters: (x0, y0) to represent the offset from your image origin to the grid origin (xs, ys) to represent a multiplication factor from your image plane to your ...
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 ...

### How to set threshold value for Hough Transform

Well, it really depends on what you expect to find in the image. The matlab function uses an example threshold of half the largest peak. What sort of images are you using this on? So, based on just ...
Accepted

### Algo Name: Detecting Elongated Shape in 2D Image by Convolution with Directed Lines

What you are essentially doing is a matched filter. However, thanks to Hough transform, your filter (line) is oriented and therefore I would call it an oriented matched filter. For generating the ...

### how to detect two parallel lines in a binary image with MATLAB

this is John BG jgb2012@sky.com 1.- Avoid doubling segments If you carry on with the code you have used in your approach: ...

### how to detect two parallel lines in a binary image with MATLAB

You mentioned the Hough transform, but your code doesn't use it. However, it can help you to find out the orientations of lines. The maximum values of the Hough transform correspond to probable lines....
Accepted

### Difference between Generalized Hough Transform and Cross-correlation Feature Matching

There is a big difference: The Hough Transform maps the input space to a parameter space, where the search takes place. This way, the run-time of the algorithm is independent of the degree of the ...

1 vote

### Circle detection opencv

I'll start with the Hough line transform. The hough transform works by creating a buffer (2 dimensional in our case) which represents all the possible lines in the image. Any possible line can be ...
1 vote