I am facing challenge to extract correct a letter from a word which are look-alike, i.e 5 & S, I & 1, 8 & S.
I applied image pre-processing techniques like Blurring, erode, dilate, normalised the noise, remove unnecessary component and text detection from the input image but after these much of pre-processing tesseract OCR isn't giving correct result. Please check attached images, *Original Image* *[image: image.png]* *Pre-processed Image* [image: image (1).png] *Detected Text* *[image: image (2).png]* *[image: image (3).png]* *Tesseract Configuration* -l eng --oem 1 --psm 7 -c tessedit_char_whitelist="ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789\n" load_system_dawg=false load_freq_dawg=false *Result of OCR*: TITLENUMBER 81003716 As we can see OCR extract S as 8 even after pre-processing and text detection. Is there anyway we can overcome this problem? *Tesseract Version*: tesseract 5.1.0-32-gf36c0 Note: Asked same question in pytesseract github repo and got suggestion to drop this question here. -- You received this message because you are subscribed to the Google Groups "tesseract-ocr" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/tesseract-ocr/72dac625-d07f-4240-9032-3fa856868b8dn%40googlegroups.com.
