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I am working on an app where you take a picture of a device and it stores the information. However, due to the device using seven segment display / LCD i am struggling to get good results.

I have used Firebase OCR, Google Vision ML Kit, And Tesseract (Tess-two).

Each of them are providing poor results, especially Tesseract considering i have trained and fine tuned it to recognise 3 types of seven segment fonts to a 0.09 error rate.

I have also tried using other peoples traineddata, such as letsgodigital

I have converted the image to greyscale and then binarized it, i have also whitelisted only numbers and still can't detect the text properly. What else can i do to improve the results?

Results below are both tesseract.

Tesseract poor resultsenter image description here

toblico999
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  • I'm sorry but can you give me the code that you use for "converted the image to greyscale and then binarized it" – Long Phan Sep 16 '21 at 08:22

1 Answers1

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Tesseract is good at recognizing documents. The example you gave contains pretty irrelevant information such as the machine and disturbing logo.

Doing the text localization to separate the seven-segment content out would be better a way to preprocess it.

Chris Tang
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