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The problem that I am running with is to extract the text out of an image and for this I have used Tesseract v3.02. The sample images from which I have to extract text are related to meter readings. Some of them are with solid sheet background and some of them have LED display. I have trained the dataset for solid sheet background and the results are some how effective.
The major problem I have now is the text images with LED/LCD background which are not recognized by Tesseract and due to this the training set isn't generated.
Can anyone guide me to the right direction on how to use Tesseract with the Seven Segment Display(LCD/LED background) or is there any other alternative that I can use instead of Tesseract.
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Create a Python tesseract script Create a project folder and add a new main.py file inside that folder. Once the application gives access to PDF files, its content will be extracted in the form of images. These images will then be processed to extract the text.
Tesseract does various image processing operations internally (using the Leptonica library) before doing the actual OCR. It generally does a very good job of this, but there will inevitably be cases where it isn't good enough, which can result in a significant reduction in accuracy.
Alphabet. In addition to the ten digits, seven-segment displays can be used to show most letters of the Latin, Cyrillic and Greek alphabets including punctuation. One such special case is the display of the letters A–F when denoting the hexadecimal values (digits) 10–15.
The line finding algorithm is one of the few parts of Tesseract that has previously been published [3]. The line finding algorithm is designed so that a skewed page can be recognized without having to de-skew, thus saving loss of image quality.
https://github.com/upupnaway/digital-display-character-rec/blob/master/digital_display_ocr.py
Did this using openCV and tesseract and the "letsgodigital" trained data
-steps include edge detection and extracting the display using the largest contour. Then threshold image using otsu or binarization and pass it through pytesseracts image_to_string function.
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