{"action":"created","issue":{"url":"https://api.github.com/repos/tesseract-ocr/tesseract/issues/1011","repository_url":"https://api.github.com/repos/tesseract-ocr/tesseract","labels_url":"https://api.github.com/repos/tesseract-ocr/tesseract/issues/1011/labels{/name}","comments_url":"https://api.github.com/repos/tesseract-ocr/tesseract/issues/1011/comments","events_url":"https://api.github.com/repos/tesseract-ocr/tesseract/issues/1011/events","html_url":"https://github.com/tesseract-ocr/tesseract/issues/1011","id":239189341,"number":1011,"title":"Incorrect recognotion of specific words - additional letters inserted","user":{"login":"vidiecan","id":332350,"avatar_url":"https://avatars2.githubusercontent.com/u/332350?v=4","gravatar_id":"","url":"https://api.github.com/users/vidiecan","html_url":"https://github.com/vidiecan","followers_url":"https://api.github.com/users/vidiecan/followers","following_url":"https://api.github.com/users/vidiecan/following{/other_user}","gists_url":"https://api.github.com/users/vidiecan/gists{/gist_id}","starred_url":"https://api.github.com/users/vidiecan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vidiecan/subscriptions","organizations_url":"https://api.github.com/users/vidiecan/orgs","repos_url":"https://api.github.com/users/vidiecan/repos","events_url":"https://api.github.com/users/vidiecan/events{/privacy}","received_events_url":"https://api.github.com/users/vidiecan/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2017-06-28T14:46:45Z","updated_at":"2018-04-20T20:39:49Z","closed_at":null,"author_association":"NONE","body":"Tesseract (master branch, tested several versions on Windows/Ubuntu) using LSTM only inserts sometimes letters where they should not be. We have observed this happening randomly (but reproducible) also with eng, ces, nor (others not tested), also with different DPI.\r\n\r\nTest case:\r\n![to recognise 1498480501215-2111908889](https://user-images.githubusercontent.com/332350/27642820-3afe616c-5c63-11e7-8f37-91c91df7e6d2.png)\r\n```\r\n./tesseract ./to.recognise.1498480501215-2111908889.png stdout --oem 1 -l ces --psm 13\r\n```\r\nExpected: Veitvetveien\r\nGot: Veitvetvelien\r\n\r\nLetter bboxes visualised below\r\n<img width=\"762\" alt=\"tesseract bug report\" src=\"https://user-images.githubusercontent.com/332350/27643336-1c6a95ee-5c64-11e7-8839-73a6a2d4d00e.png\">\r\n"},"comment":{"url":"https://api.github.com/repos/tesseract-ocr/tesseract/issues/comments/383216077","html_url":"https://github.com/tesseract-ocr/tesseract/issues/1011#issuecomment-383216077","issue_url":"https://api.github.com/repos/tesseract-ocr/tesseract/issues/1011","id":383216077,"user":{"login":"vidiecan","id":332350,"avatar_url":"https://avatars2.githubusercontent.com/u/332350?v=4","gravatar_id":"","url":"https://api.github.com/users/vidiecan","html_url":"https://github.com/vidiecan","followers_url":"https://api.github.com/users/vidiecan/followers","following_url":"https://api.github.com/users/vidiecan/following{/other_user}","gists_url":"https://api.github.com/users/vidiecan/gists{/gist_id}","starred_url":"https://api.github.com/users/vidiecan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vidiecan/subscriptions","organizations_url":"https://api.github.com/users/vidiecan/orgs","repos_url":"https://api.github.com/users/vidiecan/repos","events_url":"https://api.github.com/users/vidiecan/events{/privacy}","received_events_url":"https://api.github.com/users/vidiecan/received_events","type":"User","site_admin":false},"created_at":"2018-04-20T20:39:49Z","updated_at":"2018-04-20T20:39:49Z","author_association":"NONE","body":"For the record, you can try to fine tune/fix clear problems for example around the line \r\nhttps://github.com/tesseract-ocr/tesseract/blob/8f7be2e72c4d933c23e50cfb30e4317bd608e166/lstm/recodebeam.cpp#L266\r\nby computing the \"\"count\"\" of times a character was recognised and disregard clear outliers e.g., if a letter was seen as M 8 times and as N only once (and because of specific reasons it would still get the lowest certainty) \"transform\" N to M. \r\n\r\nHowever, better training would fix it too.\r\n\r\n"}}
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