image preprocessing methods that can be used for identification of industrial parts name (stuck or engraved) on the surface?

I am working on a project where my task is to identify machine part by its part number written on label attached to it or engraved on its surface. One such example of label and engraved part is shown in below figures.

My task is to recognise 9 or 10 alphanumerical number (03C 997 032 D in 1st image and 357 955 531 in 2nd image). This seems to be easy task however I am facing problem in distinguishing between useful information in the image and rest of the part i.e. there are many other numbers and characters in both image and I want to focus on only mentioned numbers. I tried many things but no success as of now. Does anyone know the image pre processing methods or any ML/DL model which I should apply to get desired result?

Thanks in advance!
JD

You can use OCR to the get all characters from the image and then use regular expressions to extract the desired patterns.

You can use OCR method, like Tesseract.

Maybe, you want to clean the images before running the text-recognition system, by performing some filtering to remove noise / remove extra information, such as:

• Convert to gray scale (colors are not relevant, aren't them?)
• Crop to region of interest
• Canny Filter

A good start can be one of this tutorial:

• OpenCV OCR with Tesseract (Python API)

• Recognizing text/number with OpenCV (C++ API)