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I have recently taken up film photography. Part of the workflow is to scan the images using a flatbed scanner. Unfortunately this process is very slow. Using some software (Silverfast) you make a prescan, zoom in make a more detailed pre scan, click ad drag around a rectangle which highlights the frame, do this for 12 frames, then set the software to do the full res scans.

I want to automate this process. Rather than layout where each frame is, I want to scan the whole film strip, and then use ML.Net to find each frame (X,Y coordinates of the top left corner) which I will then pass to ImageMagick to extract the actual image.

I want to use ML.Net because I am a .Net developer and may have the opportunity to use this experience later. So although example using OpenCV would be welcome, ML.Net would be preferable.

I am a bit of noob when it comes to ML stuff. My first thought is to try train a neural net, inputting the scan image and outputting the X and Y values. However that seems naive (as the image is 100s of MB in size). I imagine the there are better tool then just a raw neural net.

My searching on 'ML object recognition' didn't seem to help as the examples I found were about finding the Dog or Person in an image not a 'frame'; which could be a dog or a person.

Even a pointer in the right direction, of the correct name for this problem would be a great help.

So, what are the type of tool/functions I should I be using to try and solve this type of problem using ML.net?

DarcyThomas
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This is not so much a machine learning problem as it is an image processing problem. I would think ML.Net is quite overkill.

What you probably want is an image processing library and utilize some form of edge detection or "region of interest" detection.

For example, look at this question: Detect display corners with Emgu

Maybe I misunderstand what you want to do and you actually would benefit from machine learning; then you probably should pre process your images with an image processing library before feeding them to your model.

Hope it helps.

Karl Tillström
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