<p>I am working on analyzing data obtained from acoustic sensors. During analysis of acoustic data, I got frequency-wavenumber spectrum of acoustic data as shown below. I am looking for a technique that can estimate slope of bright feature (x-shape) in the image below. I have tested some techniques but they do not provide the required accuracy such as Radon transform and Hough transform. I wonder if there are other advanced methods in image processing that can help. <a href="https://i.sstatic.net/0pCfP.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/0pCfP.png" alt="enter image description here" /></a></p>

CC BY-SA 4.0
2024-03-04T14:20:31.593Z
Have you tried simply fitting a pair of lines to your data? (by minimizing for example the sum of distances to the nearest line)
Tassle
CC BY-SA 4.0
2024-03-05T18:31:36.033Z
@Tassle Thanks for your response. I tried to use Linear Regression to fit the data with highest value (points shown in yellow) and estimate slope while keeping intercept = 0. Actually, the method provides close value to the expected slope but the error is still high ~ 3.8 percent.
Petroleum Engineer
CC BY-SA 4.0
2024-03-05T21:56:53.523Z
I tried fitting two lines simultaneously, by minimizing the sum of the distance to the nearest of the two lines over all yellow points (using some black box optimization algorithm) and the results seem visually pretty decent: [link to image](https://www.zupimages.net/up/24/10/c7mf.png)
Tassle
CC BY-SA 4.0
2024-03-08T18:57:54.140Z
@Tassle Thanks for your response. Can you provide more details of you remethod? Which optimization algorithm that you used and what are the steps?
Petroleum Engineer
<image-processing>
How to estimate slope of a feature in image?
Petroleum Engineer
# How to estimate slope of a feature in image?

(Asked by: username_0 on 2024-03-01)

I am working on analyzing data obtained from acoustic sensors. During analysis of acoustic data, I got frequency-wavenumber spectrum of acoustic data as shown below. I am looking for a technique that can estimate slope of bright feature (x-shape) in the image below. I have tested some techniques but they do not provide the required accuracy such as Radon transform and Hough transform. I wonder if there are other advanced methods in image processing that can help. [![enter image description here](https://i.sstatic.net/0pCfP.png)](https://i.sstatic.net/0pCfP.png)

**Tags:** image-processing

> **Comments:**
> **username_1**: Have you tried simply fitting a pair of lines to your data? (by minimizing for example the sum of distances to the nearest line)  
> **username_0**: @username_1 Thanks for your response. I tried to use Linear Regression to fit the data with highest value (points shown in yellow) and estimate slope while keeping intercept = 0. Actually, the method provides close value to the expected slope but the error is still high ~ 3.8 percent.  
> **username_1**: I tried fitting two lines simultaneously, by minimizing the sum of the distance to the nearest of the two lines over all yellow points (using some black box optimization algorithm) and the results seem visually pretty decent: [link to image](https://www.zupimages.net/up/24/10/c7mf.png)  
> **username_0**: @username_1 Thanks for your response. Can you provide more details of you remethod? Which optimization algorithm that you used and what are the steps?  

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## 0 answers

