I use Tesseract and JNA wrapper Tess4J for my Java application.
I try to OCR jpeg images with 120 DPI. The output text is a pretty low quality and a lot of important words are not recognized properly. I think the main issue is in my input images because of 120 DPI. I tried to rescale the images x2. It helped but a very little bit. The result is still so far from perfect.
Right now I'm looking for other options with Tesseract in order to improve the OCR quality of my data.
My images contain health care information so I wondering - if I'll provide the custom dictionary with medical words, will it help to improve the quality of OCR? If so, if I'll provide a dictionary with 100k terms - how it will affect the performance of Tesseract?
Please show how to provide this dictionary with Tess4J.
What other options I should also try?
Related
I use tesseract engine to OCR my images as below.
image1 to OCR
image2 to OCR
I used eng lang and have configured the engine with a white list of chars: "0123456789abcdefghijklmnopqrstuvwxyz"
pOCREngine->SetVariable("tessedit_char_whitelist", "0123456789abcdefghijklmnopqrstuvwxyz");
The accuracy is not good, around 10% or so. I have tried to train the engine with ~200 of such images and combine the trained data with eng+mytrainedfont. The accuracy was not improved.
Does anyone have any idea to improve OCR of such images? Thanks in advanced.
The images you provided are difficult to get a 100% accuracy on when I tried it. To improve tesseract ocr you will need to apply some image processing methods.
I used a Gaussian filter on both and used a Maximum filter after that to reduce the noise. After that I made the images binary.
I'm using tesseract ocr in c++ and I'm using OpenCV libraries for image processing. I tested the following images with the following results:
image1
result: yfsxf
image2
result: 26ww(
Hope this gives you an idea on how to improve tesseract results. Unfortunately the images you provided are a bit tough to read with tesseract.
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)
I have a pdf of 100+ handwritten pages that I need to convert to machine readable text. So far I have tried tesseract and a free online tool with no success. The output seems to be jibberish.
tesseract myscan.png out -l eng
I've attached one example page. It contains both text, mathematical symbols (eg. integral sign) and occasionally pictures.
Maybe I'm using tesseract wrong? Could anyone try and get a decent output off this?
I use http://www.techsupportalert.com/best-free-ocr-software.htm
Watch out for the installer trying to load you up with other stuff
When it works, it just gives you bits to copy and paste.
But don't rush to download this one, try your's again first.
The problem likely isn't with the software, it's probably your input.
Scan at 600 dpi.
Try to increase the contrast and sharpen the image. The thinner and more defined from the background that the letters are, and the clearer the interspacing of the loops are, the better your chance of OCR capture.
These adjustments are best made in your original scanning software. 8MP or better camera can also make the scan.
Use GIMP to tweak after the scan.
I'm working on getting the Lincoln font to work in Tesseract, and I'm getting abysmal results, even after going through the wildly complicated training process.
This is what the font looks like, so yeah, it's a bit tricky:
I've carefully made a training image, and then used that to make a box file. The training image is here (25MB!). The image is 300 DPI, and has representative characters nicely spaced out vertically and horizontally.
I made a box file for the training image, and it worked properly. I've verified that it's correct using a box file editor.
I took this box file/tif file, and used it to create training data. I did likewise with the 30 or so other sample images/fonts provided by Tesseract.
I created the unicharset file.
I created a font_properties file. There's no guidance on the site about when fraktur should be used. So I've tried it both this way (fraktur on for Lincoln):
eng.lincoln.box 0 0 0 0 1
And this way (fraktur off):
eng.lincoln.box 0 0 0 0 0
And finally, I've tried this with and without dictionary files. When I used dictionary files, they were the wordmap from my search engine, Sphinx, and they have about 15K common words and about 20K uncommon ones.
In all cases, when I try to OCR the first couple lines of this file (3MB), the quality is abysmal. Rather than getting:
United States Court of Appeals
for the Federal Circuit
I get:
OniteiJ %tates C0urt of QppeaIs
for the jfeI1eraICircuit
Why?
I think you'll need a lot more samples (letters) and better training images (clean background, grayscale, 300 DPI, etc.). And try to train with only one font (for instance, Lincoln) first. You can use jTessBoxEditor tool to generate your training images and edit the box files.
Once you master the training process, you can add other fonts to your training. You can test the success of the resultant language data by using it in performing OCR on the training image itself -- the recognition rates should be high.
The font names in font_properties should be like:
lincoln 0 0 0 0 1
I am not a Tesseract expert but I have evaluated nearly every OCR engine available and my comments are based on my experience over the years of analysing OCR errors.
Just wondering why your image has speckles in the background and not a pure white background. I don't know how Tesseract or the training tool works but the background could be causing some problems.
Just reading the sample page is difficult and requires a large amount of concentration. Characters such as F and I are very similar as are U and N. Tesseract like many OCR engines would be using many different techniques to recognise a character and there is not a whole lot difference between many of these characters in terms of the strokes and curves used in the font.
These characters, especially the uppercase characters would confuse many different matching algorithms just because they are so different to standard Latin / Roman type characters. This shows through in your results ie. All capital letters have an OCR error.
I'm trying to use Tesseract-OCR to detect the text of images with pure text in it but these text has a handwritten font called Journal.
Example:
The result is not the best:
Maxima! size` W (35)
Is there any possibility to improve the result or rather to get the exact result?
I am surprised Tesseract is doing so well. With a little bit of training you should be able to train the lower case 'l' to be recognised correctly.
The main problem you have is the top of the large T character. The horizontal line extends across 2 (possibly 3) other character cells and this would cause a problem for any OCR engine when it tries to segment the characters for recognition. Training may be able to help in this case.
The next problem is the . and : which are very light/thin and are possibly being removed with image pre-processing before the OCR even starts.
Overall the only chance to improve the results with Tesseract would be to investigate training. Here are some links which may help.
Alternative to Tesseract OCR Training?
Tesseract OCR Library learning font
Tesseract confuses two numbers
Like Andrew Cash mentioned, it'll be very hard to perform OCR for that T letter because of its intersection with a number of next characters.
For results improvement you may want to try a more accurate SDK. Have a look at ABBYY Cloud OCR SDK, it's a cloud-based OCR SDK recently launched by ABBYY. It's in beta, so for now it's totally free to use. I work # ABBYY and can provide you additional info on our products if necessary. I've sent the image you've attached to our SDK and got this response:
Maximal size: lall (35)