These results are for PSM=1, I think I have tried other values, but I haven't notice any improvements. https://github.com/apismensky/ocr_id/blob/main/ocr_id.py#L81
Regards, Alexey On Monday, September 4, 2023 at 2:02:27 AM UTC-6 nguyenng...@gmail.com wrote: > Hi, > I would like to hear other's opinions on your questions too. > In my case, when I try using Tesseract for Japan train tickets, I have to > do a lot of steps for preprocessing (remove background colors, noise + line > removal, increase contrast, etc.) to get satisfactory results. > I am sure what you are doing (locating text boxes, extracting them, and > feeding them one by one to tesseract) can get better accuracy results. > However, when the number of text boxes increases, it will undoubtedly > affect your performance. > Could you share the PSM mode for getting those text boxes' locations ? I > usually use the AUTO_OSD to get the boxes and expand them a bit at the > edges before passing them to Tesseract. > > Regards > Hai > > On Saturday, September 2, 2023 at 7:03:49 AM UTC+9 apism...@gmail.com > wrote: > >> I'm looking into OCR for ID cards and drivers licenses, and I found out >> that tesseract performs relatively poor on ID cards, compared to other OCR >> solutions. For this original image: >> https://github.com/apismensky/ocr_id/blob/main/images/boxes_easy/AR.png >> the results are: >> >> tesseract: "4d DL 999 as = Ne allo) 2NICK © , q 12 RESTR oe } lick: 5 DD >> 8888888888 <(888)%20888-8888> 1234 SZ" >> easyocr: '''9 , ARKANSAS DRIVER'S LICENSE CLAss D 4d DLN 999999999 3 DOB >> 03/05/1960 ] 2 SCKPLE 123 NORTH STREET CITY AR 12345 ISS 4b EXP 03/05/2018 >> 03/05/2026 15 SEX 16 HGT 18 EYES 5'-10" BRO 9a END NONE 12 RESTR NONE Ylck >> Sorble DD 8888888888 1234 THE''' >> google cloud vision: """SARKANSAS\nSAMPLE\nSTATE O\n9 CLASS D\n4d DLN >> 9999999993 DOB 03/05/1960\nNick Sample\nDRIVER'S LICENSE\n1 SAMPLE\n2 >> NICK\n8 123 NORTH STREET\nCITY, AR 12345\n4a ISS\n03/05/2018\n15 SEX 16 >> HGT\nM\n5'-10\"\nGREAT SE\n9a END NONE\n12 RESTR NONE\n5 DD 8888888888 >> 1234\n4b EXP\n03/05/2026 MS60\n18 EYES\nBRO\nRKANSAS\n0""" >> >> and word accuracy is: >> >> tesseract | easyocr | google >> words 10.34% | 68.97% | 82.76% >> >> This is "out if the box" performance, without any preprocessing. I'm not >> surprised that google vision is that good compared to others, but easyocr, >> which is another open source solution performs much better than tesseract >> is this case. I have the whole project dedicated to this, and all other >> results are much better for easyocr: >> https://github.com/apismensky/ocr_id/blob/main/result.json, all input >> files are files in >> https://github.com/apismensky/ocr_id/tree/main/images/sources >> After digging into it for a little bit, I suspect that bounding box >> detection is much better in google ( >> https://github.com/apismensky/ocr_id/blob/main/images/boxes_google/AR.png) >> and easyocr ( >> https://github.com/apismensky/ocr_id/blob/main/images/boxes_easy/AR.png), >> than in tesseract ( >> https://github.com/apismensky/ocr_id/blob/main/images/boxes_tesseract/AR.png). >> >> >> I'm pretty sure, about this, cause when I manually cut the text boxes and >> feed them to tesseract it works much better. >> >> >> Now questions: >> >> - What is the part of the codebase in tesseract that is responsible for >> text detection and which algorithm is it using? >> - What is impacting bounding box detection in tesseract so it fails on >> these types of images (complex layouts / background noise... etc) >> - Is it possible to use the same text detection procedure as easyocr or >> improve the existing one? >> - Maybe possible to switch text detection algo based on the image type or >> make it pluggable where user can configure from several options A,B,C... >> >> >> Thanks. >> > -- 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 tesseract-ocr+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/tesseract-ocr/44a60dea-f76b-409d-8bff-b764427700c2n%40googlegroups.com.
