Java OCR Ron Cemers Blog. Several years back, I was working on an imaging project in Java which was going to require some Optical Character Recognition OCR functionality. After an exhaustive search, I could find nothing to fit the bill. My requirements were Must be written in Java. Optical character recognition also optical character reader, OCR is the mechanical or electronic conversion of images of typed, handwritten or printed text into. DeCaptcher is a CAPTCHA solving service. It helps SEO masters and regular users to automate their online routine by decoding their CAPTCHAs. Captcha Ocr Software' title='Captcha Ocr Software' />Several years back, I was working on an imaging project in Java which was going to require some Optical Character Recognition OCR functionality. ReCAPTCHA ist ein CaptchaDienst. Der vollautomatische ffentliche TuringTest soll sicherstellen, dass eine bestimmte Handlung im Internet von einem Menschen und. We offer Fastest, cheapest captcha solving service powered by OCR and human. Our OCR technology decode captchas extremely fast and accurately. Hard captchas is solved. Must be freely redistributable, with or without source code. Must not be proprietary. Must be able to recognize the fonts of various printers, even if that means that it has to be trained for each new font. Must be reasonably fast. I never found anything that met my requirements, so I set about developing something to fit the bill. What I ended up developing, is a generic, trainable OCR package that does a fairly decent job of decoding printed text, as long as it has been trained for the fonts it is expected to recognize. How it Works. This OCR engine is implemented as a Java library, along with a demo application which shows the library in action. The core concept, at the character level, is image matching with automatic position and aspect ratio correction, using a least square error matching algorithm. It is a very simple yet reasonably effective implementation. The Training Phase. Training consists of the following steps Printing out the characters which it is expected to recognize. Scanning those characters into an image. Cropping the image down so that it includes only the training characters. Telling the OCR engine to use the resulting training image, and specifying which characters the image contains. Character Recognition. The general steps used by this OCR engine for converting a scanned document to text are Load training images. RJEX6vxqk8/hqdefault.jpg' alt='Captcha Ocr Software' title='Captcha Ocr Software' />Load the scanned image of the document to be converted to text. Convert the scanned image to grayscale. Includes demonstrations, research papers, and news. Armando Huerta Drawings. Filter the scanned image using a low pass Finite Impulse Response FIR filter to remove dust. Break the document into lines of text, based on whitespace between the text lines. Break each line into characters, based on whitespace between the characters using the average character width, determine where spaces occur within the line. For each character, determine the most closely matching character from the training images and append that to the output text for each space, append a space character to the output text. Output the accumulated text. If there are any more scanned images to be converted to text, return to step 2. Applications. This is a generic, trainable OCR engine. By default, it knows nothing except how to attempt to filterclean up dust, convert to greyscale, break the document into lines, break the lines into characters, compare each character against known characters in user supplied training images, and output the closest matches as text. The engine was originally written to digitize documents or specific sections of documents which were printed with a handful of known fonts for which it could be trained, in order to minimize the error. Digitization was not intended to be 1. It was intended to be used in a document imaging system. Accuracy and Performance. With the simple documents with which it was tested, this OCR engine has compared favorably against the open source OCR package GOCR. It translated images to text with at least comparable accuracy to GOCR, and was in the same ballpark as far as speed, if not somewhat faster than GOCR. Fortran Programs For Physics. Extensive comparisons were not performed. Getting Started. The following instructions assume youre running on a Linux box, with a reasonably recent version of Suns JDK installed. You can get the JDK at http www. Be sure to remove any fake java packages that come with your Linux distribution. If you install Open. Office, chances are youll get a counterfeit GNU Java implementation which does not conform to Suns Java specification, and is actually quite outdated as well. Unfortunately, Open. Office has dependencies on this package. To get rid of it, youll need to do something like this before installing Suns JDK rpm e nodeps java 1. NOTE This may BREAK your Open. Office installation, at least until you install the Sun JDK to replace the missing Java functionality. But hey, the Open. Office guys should know better than to force someone to install an illegitimate Java knock off, especially since Open. Office is operated by Sun, who created the real Java in the first place. Theres just no excuse. As a potential alternative, if youre more skilled than I am with the Linux alternatives package, you could use it to fix up the symlinks under etcalternatives to point to the real JDK without uninstalling the GNU Java knock off. However, youd have to be careful about software updates to the GNU Java knock off accidentally resetting these symlinks, thereby breaking the real JDK. What a mess. Sun should really go after these guys for creating executables with the same names as Suns, and purposely interfering with the distribution of Suns legitimite Java implementation. After all, isnt that what Microsoft did with their fake Java implementation Bad actions are bad, no matter whos doing them. But I digress. So, back to the OCR engine. When you download and unpack the tarball, youll have an ocr directory. Under it youll find these scripts compile compiles the Java files into class files in the classes directorycreate. Jars creates ocr. OCR functionality using any of several test images and corresponding training images. Compiling. The source code shouldalready be compiled, and there should be an ocr. If so, you can proceed. If not, or if you need to rebuild after making a change to the source code, just do the following. Jars. Assuming there are no errors, youll get freshly compiled classes and a new ocr. Running the Demos. If you look under the ocr. Tests directory, there are several png and jpg files. Each of these is an image which contains text, and can be used to demonstrate the functionality of the OCR engine. To test the OCR engine on an image, do something like this. Testsascii. Sentence. Notice that there is also a directory named ocr. Teststraining. Images. This contains the font samples that are used to train the OCR engine in the demo application, so that it can recognize the fonts that were used to create the test images in the ocr. Tests directory. If you look at the srccomroncemerocrOCRScanner. Demo. java source file, in the load. Training. Images function, youll see that the demo app is loading up each of these training images and telling the OCR engine which character ranges are contained in each image. The OCR engine then uses these images to match against each character in the source image, in order to convert the source image into text. Donkey Kong Arcade Game Full Version. Using the Code in your Program. To use the code in your own program, put ocr. OCRScanner. Demo. Feel free to look at the other source files, if youre interested in the inner workings of the OCR engine. The concepts are fairly simple, yet reasonably effective. License. I originally released this engine under the GPL license, version 2. However, I felt it would be more commercially friendly if it were re released under the BSD license. As of may 6, 2. 01. Ive created a project page on Source. Forge, changed the license to BSD, and uploaded the whole thing to the Source. Forge Subversion repository. Source. Forge Project Page. The new Java. OCR Source. Forge project is located here http javaocr. Feedback. As always, Im interested in your feedback, suggestions for improvement, use cases, success stories, or whatever.