I've been reading (and trying) OCR programs suggested in previous answers but I'm still without a clear answer to my problem.
I need to recognize handwritten English text. The text would be multiple lines but each line is only one or two words length. The text is from a different person at time. I could ask that person to provide a training file (e.g. with the alphabet and 0-9 numbers) but I cannot really ask for a much more complicated training than this.
I need to integrate the recognition as part of another (Java) application but the solution doesn't need to be Java. I can just execute it from Java and get the results from a text file.
Any recommendations?
I've already tested Tesseract (bad results without training and training looks quite complex). Java OCR looked like the perfect solution (simple training, open source and Java) but it doesn't work well even with their own examples (anybody has had a better experiencie?). GOCR does not seem very active.
Of course I prefer free solutions but this is not a MUST (though the problem I see with a commercial option is that I must be able to integrate it in my own app which will be offered as SaaS)
From my experience ABBYY is one of the best for handwriting recognition, even without training. (It's possibly one of the most expensive too, though...) They have an SDK for Java.
http://www.abbyy.com
With a free trial, it's definately worth a look!
I am on the lookout for a handwritten text recognition software. So far the only one giving better results than even abby 11 has been SimpleOCR using the same text for both, which is a freeware for ocr but a 14 day trial for HCR!
I know I am answering after nearly 6 years. But if anyone's still looking, try using tensorflow. Their website has a simple example for handwritten digit recognition(MNIST). You can use this example and implement it for handwritten alphabet recognition (you need training data for this, I used NIST special Database 19 to get this data).
Related
I am working on an OCR related android app and I need to use multivariate logistic regressions for the classification of alphabets. My question is that that can I use Stanford classifier(http://nlp.stanford.edu/software/classifier.shtml) for character recognition? If it can train on a dataset of images? And if I can't then please suggest me a JAVA library for the purpose.
Great minds think alike. I was wondering the same thing. Specifically for OCR.
Even though it's almost a year after you asked your question.
It sounds simple enough; all you would need to do is normalize each character into a 5x7 array (or maybe 64x128), and then classify into the 26 upper and 26 lower case characters; plus 10 digits and 31 punctuation glyphs on a keyboard... Seems doable. Maybe when I get a round tuit...
It turns out that there is a Java library for OCR https://sourceforge.net/projects/javaocr/ and it's called Java OCR (surprise! :-) ). The only problem is that:
1. It doesn't work out of the box. It needs to be trained.
2. The documentation isn't very good.
3. People have had trouble getting it to work.
Good luck.
I tried to improved the results of OpenSource OCR software. I'm using tessaract, because I find it still produces better results than gocr, but with bad quality input it has huge problems. So I tried to prepocess the image with various tools I found in the internet:
unpaper
Fred's ImageMagick Scripts: TEXTCLEANER
manuall using GIMP
But I was not able to get good results with this bad test document: (really just for test, I don't need to content of this file)
http://9gag.com/gag/aBrG8w2/employee-handbook
This online service works surprisingly good with this test document:
http://www.onlineocr.net/
I'm wonderung if it is possible using smart preprocessing to get similar results with tesseract. Are the OpenSource OCR engines really so bad compared to commercial ones? Even google uses tesseract to scan documents, so I was expecting more...
Tesseract's precision in recognition is a little bit lower than the precision of the best commercial one (Abbyy FineReader), but it's more flexible because of its nature.
This flexibility entail sometimes some preprocessing, because it's not possible for Tesseract to manage each situation.
Actually is used by google because is Google its main sponsor!
The first thing you could do is to try to expand the text in order to have at least 20 pixel wide characters or more. Since Tesseract works using as features the main segments of the characters' borders, it needs to have a bigger characters' size comparing with other algorithms.
Another thing that you could try, always referring to the test document you mentioned, is to binarize your image with an adaptive thresholding method (here you can find some infos about that https://dsp.stackexchange.com/a/2504), because some changes in the illumination are present. Tesseract binarizes the image internally, but this could be the case when it fails to do that (it's similar to the example here Improving the quality of the output with Tesseract, where you can also find some other useful informations)
For the past 3 months I've been trying to train the Tesseract
With identifying a collection of images I've had, due a real lack
of proper documentation, and very high level of complexity I'm starting to
give up on Tesseract as a solution.
I'm looking for an alternative, which would be relatively pain free
for training, I'm not looking to rediscover the wheel here.
If there isn't anything free, I guess paid solutions would
have to do (nothing above 200$)
Based on your comment, all you need is to scan relatively small amount of documents with almost 100% accuracy and your budget is about 200$
Well, the answer is simple then. You don't need any programming solution. Just buy quality commercial OCR product, f.e. ABBYY FineReader (disclaimer: I work for ABBYY). It has different prices in different regions, but I guess it is somewhere in about your budget.
Commercial desktop OCR product will provide you out-of-the box almost 100% accuracy on typical languages. Also they have convenient manual verification tools to fix all remaining errors. Typically they support whole variety of modern fonts, but if your font is not trivial, they do have font training utility for that.
I do think that is optimal solution for you.
UPDATE: Linux platform.
Unfortunately, there is almost no choice of high quality OCR products for Linux, sorry. The only one I know is from ABBYY: http://ocr4linux.com/en:start but it does not have UI, verification and font training. But at least you can give it a try to see if it will give you good enough accuracy as it is, which may happen to be the case.
You can use jTessBoxEditor to edit the box files you generate. Bundled with it is a PowerShell script to automate box file and final .traineddata file generation.
I need an open OCR library which is able to scan complex printed math formulas (for example some formulas which were generated via LaTeX). I want to get some LaTeX-like output (or just some AST-like data).
Is there something like this already? Or are current OCR technics just able to parse line-oriented text?
(Note that I also posted this question on Metaoptimize because some people there might have additional knowledge.)
The problem was also described by OpenAI as im2latex.
SESHAT is a open source system written in C++ for recognizing handwritten mathematical expressions. SESHAT was developed as part of a PhD thesis at the PRHLT research center at Universitat Politècnica de València.
An online demo:http://cat.prhlt.upv.es/mer/
The source: https://github.com/falvaro/seshat
Seshat is an open-source system for recognizing handwritten mathematical expressions. Given a sample represented as a sequence of strokes, the parser is able to convert it to LaTeX or other formats like InkML or MathML.
According to the answers on Metaoptimize and the discussion on the Tesseract mailinglist, there doesn't seem to be an open/free solution yet which can do that.
The only solution which seems to be able to do it (but I cannot verify as it is Windows-only and non-free) is, like a few other people have mentioned, the InftyProject.
InftyReader is the only one I'm aware of. It is NOT free software (it seems the money goes to a non-profit org, IIRC).
http://www.sciaccess.net/en/InftyReader/
I don't know why PDF can't have metadata in LaTeX? As in: put the LaTeX equation in it! Is this so hard? (I dunno anything about PDF syntax, but I imagine it can be done).
LaTeX syntax is THE ONE TRIED AND TRUE STANDARD for mathematics notation. It seems amazingly stupid that folks that produced MathML and other stuff don't take this in consideration. InftyReader generates MathML or LaTeX syntax.
If I want HTML (pure) I then use TTH to read the LaTeX syntax. Just works.
ABBYY FineReader (a great OCR program) claims you can train the software for Math, but this is immensely braindead (who has the time?)
And Unicode has lots of math symbols. That today's OCR readers can't grok them shows the sorry state of software and the brain deficit in this activity.
As to "one symbol at a time", TeX obviously has rules as to where it will place symbols. They can't write software that know those rules?! TeX is even public domain! They can just "use it" in their comercial products.
Check out "Web Equation." It can convert handwritten equations to LaTeX, MathML, or SymbolTree. I'm not sure if the engine is open source.
Considering that current technologies read one symbol at a time (see http://detexify.kirelabs.org/classify.html), I doubt there is an OCR for full mathematical equations.
Infty works fairly well. My former company integrated it into an application that reads equations out loud for blind people and is getting good feedback from users.
http://www.inftyproject.org/en/download.html
Since the output from math OCR for complex formulas will likely have bugs -- even humans have trouble with it -- you will have to proofread th results, at least if they matter. The (human) proofreader will then have to correct the results, meaning you need to have a math formula editor. Given the effort needed by humans, the probably limited corpus of complex formulas, you might find it easier to assign the task to humans.
As a research problem, reading math via OCR is fun -- you need a formalism for 2-D grammars plus a symbol recognizer.
In addition to references already mentioned here, why not google for this? There is work that was done at Caltech, Rochester, U. Waterloo, and UC Berkeley. How much of it is ready to use out of the box? Dunno.
As of August 2019, there are a few options, depending on what you need:
For converting printed math equations/formulas to LaTex, Mathpix is absolutely the best choice. It's free.
For converting handwritten math to LaTex or printed math, MyScript is the best option, although its app costs a few dollars.
You know, there's an application in Win7 just for that: Math Input Panel. It even handles handwritten input (it's actually made for this). Give it a shot if you have Win7, it's free!
there is this great short video: http://www.youtube.com/watch?v=LAJm3J36tLQ
explaining how you can train your Fine Reader to recognize math formulas. If you use Fine Reader already, better to stick with one tool. Of course it is not free ware :(
I have to pull two pre-printed (not hand-written) fields out of a paper form, such that it can be automatically routed after being scanned. The fields contain batch and item identifiers, like "GG-9192" or "EPN/245G".
I've tried the following software:
Tesseract-OCR
Cuneiform
Canon ImageRunner built-in OCR
Asprise OCR Java API (demo)
I've tried the following settings:
Scanning at resolutions of 300dpi and 600dpi
Tried different fonts, including OCR-A and OCR-B.
In all cases output was pretty much all over the place. I can kick back documents for which I can't properly extract the necessary information, but I'm thinking it's going to be at least half of them. I considered some sort of fuzzy logic based on known values in a database, but sometimes these identifiers can differ by a single character, like "123G" and "123C".
Is this a lost cause? Perhaps OCR just isn't mature enough to handle a requirement of this nature? What other techniques might you recommend? Barcodes?
Edit: the containing application is in Java, so any recommendations for which there are free or cheap Java-based APIs for would help.
Edit 2: if anyone is interested...without any special tuning, Cuneiform for Linux and the Canon ImageRunner worked best, with Tesserect-OCR and Asprise Java API producing the worst results...none of the four was acceptable for anything but standard document search grade OCR. I'm beginning to think that this isn't going to work out.
If you have control over the fields, why use a human-readable format in the first place? For scanning, it seems like a QR Code, or something similar would be best. It is marked for orientation, and has some built-in error correction.
http://en.wikipedia.org/wiki/QR_Code
I started digging for products starting with Tomato's suggestion. I tried ABBYY and CVISION. Both have products that can automate OCR:
CVISION Maestro Recognition Server 4.0
ABBYY Recognition Server 2.0
In addition, ABBYY has SDKs for various platforms, and CVISION has an SDK that appears to work with at least VB/VC++.
I haven't tried either SDK yet, and am not sure it's necessary for my project. All I need is PDFs coming in that I can extract the text from. I did however try CVISION's server product and with the OCR on its most accurate settings, it worked really well. I haven't tried ABBYY's server product yet because I have to go through a reseller to get a trial. I'm in the process of doing so, but if it starts getting annoying I'm probably going to go with CVISION. I did try ABBYY's FineReader standalone product, and it worked very well, so I assume that their server product would also.