Image processing problem (counting is hard )

In summary, the speaker is looking for a way to collect data from a large number of images of horizontal lines. They have attached a sample with edges of nine lines and want to measure the width of each line and export the data for later processing. However, the images are noisy, with small "holes" in the lines, and the speaker needs a method for filtering out the noise. They suggest using a pattern recognition algorithm, but are unsure of how to set it up. They are looking for ideas and help in finding a solution.
  • #1
the.drizzle
10
0
Hiya! Long time registrant, have not used these forums is years though...

Anyhow, the problem I have is that I need to collect data from a very large number of images that are essentially horizontal lines on a page. I've attached a sample here, which has been processed to find the edges of the lines--the attached file shows the edges of nine lines, unevenly spaced. I want to measure the width of each line over all pixels, and export that data to an external file for later processing.

In theory this would be quite simple; start at the top (or bottom) of the page, scan down (up) until one hits a red pixel, record that position, record the position of the next one, and the difference gives us the width for that line at that position. We then continue down (up) for all n-lines, and across the page as well.

The tricky bit though is that images are noisy. That is, there are small "holes" in the lines and a few outside them as well. What I need to do is figure out a method of deciding which bits are noise, and which bits are not. I can't manually delete the "holes" from the data set, as there are literally thousands of these to process, and that would take weeks.

I'm thinking some sort of pattern recognition algorithm would be a good idea, but I'm not sure how they work...

Thus, what I'm looking for here are some possible ideas as to how one might go about filtering the noise from the image in some manner, or pehaps an algorithm that may be able to decide which points are line and which ones are noise when scanning the image. I've been at this for some time now, and am running out of ideas...

Thanks in advance for any help!
 

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  • #2
OK, got it sorted out and churning away nicely.
 
  • #3
Yep. the image pattern recognition algorithm can influence the image scanning effection, as for how to set the image recognition algorithm and more info algotithm, you can have a search.
 

FAQ: Image processing problem (counting is hard )

What is image processing?

Image processing is the use of algorithms and techniques to analyze, manipulate, and enhance digital images. This can include tasks such as image restoration, image enhancement, and image recognition.

Why is counting in image processing considered difficult?

Counting in image processing can be difficult due to various factors such as image quality, background noise, and variations in lighting. These can all affect the accuracy of the counting algorithm and make it challenging to accurately count objects in an image.

What are some common challenges in counting objects in images?

Some common challenges in counting objects in images include occlusion (objects blocking each other), overlapping objects, varying sizes and shapes of objects, and variations in lighting and background.

What techniques are commonly used to improve counting accuracy in image processing?

Some techniques that can improve counting accuracy in image processing include pre-processing of images to remove noise, using advanced algorithms such as machine learning, and implementing post-processing steps to refine the results.

How can image processing be used for counting in scientific research?

Image processing can be used for counting in scientific research in a variety of fields such as biology, medicine, and environmental science. It allows for efficient and accurate counting of objects in large datasets, providing valuable insights for research and analysis.

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