LEAD Technologies Received Four ComponentSource Awards

ComponentSource has been our global distributor since 1995. Starting in 2006, ComponentSource started awarding top publishers and software based on sales for the year. LEAD and LEADTOOLS have received an award every year since.

There are two sets of awards: ComponentSource Bestselling Product Awards for 2014-2015 and ComponentSource Bestselling Publisher Awards for 2014-2015. The allocation of the awards was calculated based on ComponentSource global sales orders during 2014.

For 2014-2015, LEAD Technologies was recognized as a Top 25 Bestselling Publisher. LEADTOOLS Document Imaging Suite, Document Imaging and PACS Imaging were recognized as Top 100 Bestselling Products.

Publisher Award

  • LEAD Technologies – Top 25 Publisher Award

Product Awards

  • LEADTOOLS Document Imaging Suite SDK – Top 100 Product Award
  • LEADTOOLS Document Imaging SDK – Top 100 Product Award
  • LEADTOOLS PACS Imaging SDK – Top 100 Product Award

See the Publisher Awards page:

See the Product Awards page:

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Major Updates to Document and Medical SDKs Are Available

LEADTOOLS v19 icon

LEAD Technologies is pleased to announce the release of a major update to the LEADTOOLS Document and Medical Product lines. The headliner of this update is the Advantage OCR engine, which boasts a plethora of improvements which contribute to a significant increase in overall speed and accuracy.

Keep reading below to see a list of all the improvements in this update. You can also read the official press release.

What’s new in the LEADTOOLS Document Engine


  • 82% speed boost to overall performance of Advantage OCR engine
  • Faster page insertion
  • Improved recognition accuracy
  • Higher accuracy of font-size detection through improved noise removal
  • Enhanced spell checker speed by 100%
  • Optimized memory usage during AutoZone
  • Table detection 50% faster


  • Parse, edit and save modified PDF forms
  • Read and write PDF Digital Signature
  • Native memory support
  • Memory enhancements when loading large PDF documents
  • Optimized extraction of PDF file information including internal links, bookmarks, etc.
  • Speed improvements to loading and saving SVG PDF documents
  • Lower memory consumption when loading raster PDF

Document Viewer and Converter

  • Faster SVG rendering
  • Designer support for Leadtools.Controls.Winforms
  • Load and save from SharePoint, OneDrive and Google Docs
  • Native support for MOBI and ePUB format
  • Shape and drawing support for DOC/DOCX
  • Across-the-board improvements to Office, HTML, MOBI and ePUB formats
  • HTML5 / JavaScript Document Viewer demo redesigned to use ASP.NET MVC
  • Converted Document REST service to ASP.NET
  • New .NET WinForms demo for viewing either Raster or SVG


  • Dashed line support for HTML5 / JavaScript
  • Region / language support when loading and saving
  • Improved custom annotation pictures
  • Add padding to all sides of an object regardless of alignment
  • Automatically rotate annotation images and text with viewer rotation
  • Load annotations directly from PDF and TIFF files
  • New legacy framework for loading and saving old versions of LEADTOOLS annotations
  • Improved annotation realization (burning) for all platforms

Additional Document Updates

What’s new in the LEADTOOLS Medical Engine


  • Updated to 2015c DICOM Specifications
  • Native Model (XML and JSON) support
  • Import and export XML format (PS3.19)
  • Import and export to DICOM JSON model (PS3.18)
  • Improved support for inserting large data

HTML5 Medical Viewer

  • Restrict user access to records at the Patient level
  • Improved sorting options and display
  • Split series into multiple stacks
  • Load all images without scrolling
  • Improved memory usage and speed
  • Pinch-zoom support
  • Image Projection Orientation support
  • Burn tags (overlays) onto image — All platforms

DICOM Storage Server

  • Show live connections in server UI
  • New cancel-forward and cancel-clean options
  • AE Title Aliases

Medical Workstation

  • Configuration options
    • Pagination
    • Export with Anonymization
  • Encapsulated PDF support

What’s new in the LEADTOOLS Imaging Engine

  • Redesigned, fully customizable HTML5 Web Scanning Service
  • Enhanced the TWAIN engine providing 64-bit apps access to 32-bit drivers
  • Salt and Pepper noise removal image processing function
  • Animated GIF support for HTML5 / JavaScript Viewer
  • Resample color images in HTML5 / JavaScript Viewer
  • Support for Pan Window in WPF Leadtools.Windows.Controls
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Get Contact Info from Business Card with OCR: 25 Projects in 25 Days

OCR Zones
OCR Zones
OCR Results
OCR Results

As part of the LEAD Technologies 25th anniversary, we are creating 25 projects in 25 days to celebrate LEAD’s depth of features and ease of use. Today’s project comes from Hadi.

If you’ve been keeping track, this is actually our 25th project and the last one in our #LEAD25 series. But don’t be sad, we post examples like these to our blog and forums on a regular basis so keep in touch! If you missed any of them, take a look back at our series introduction where we’ve kept a running list as each project was posted.

What it Does

This ASP.NET C# application recognizes zones of text from business cards using LEADTOOLS Version 19.

Features Used

Development Progress Journal

Hello, my name is Hadi I am writing a sample application that will allow users to upload an image of a business card and then let them select zones to be recognized using OCR for uploading the text as a contact.

I am using an ASP.NET application so that I can combine server-side C# code in the code behind and HTML5 and JavaScript on the client side. I will use the LEADTOOLS JavaScript ImageViewer and Annotation SDK in order to display the zones the user wants to recognize from the business card and on the server side I will use the .NET Annotations and OCR SDK.

To start I will need to create the aspx Default page for the user interface. I want the user to be able to upload an image, display the image, and then allow them to add/remove annotation rectangles to depict the desired zones.

On the server side, I want to be able to take the uploaded file and use the LEADTOOLS OCR AutoZone method in order to have some premade zones available for the user to manipulate on the front end. I also need to be sure that the file uploaded is a valid MIME type for display in the browser and if not convert it to one.

The AutoZone method gave me the zones and I used the LEADTOOLS Annotations to save an XML file that contains the zone bounds. This will let me easily display the zones to the user on the front end. I need to add a function in the JavaScript that will load the image and the XML zone file for displaying. I need to call the JavaScript from the server, so I used the ClientScriptManager.RegisterStartupScript method from the System.Web.Ui namespace.

Now that I have the XML filename in the JavaScript, I need to load it with AnnCodecs from the LEADTOOLS.Annotations.Core.JS namespace. I am using the XMLHttpRequest open and send methods to open the XML file and process the results in the onreadystatechange event. To load the image, I just set the ImageViewer.ImageUrl property to the file of the image I passed to the function. It was very easy to load the image with the LEADTOOLS ImageViewer:

Documentation: ImageViewer

Now that most of the functionality is implemented, I am going to add additional features that will allow the user to manipulate the zones. I want the user to be able to set the name of the zone so that they can know what the field belongs to. For this I am using the AnnObject.AnnLabel property:

Documentation: AnnLabel

A couple other features I have added allow the user to delete selected zones or clear all the zones. This is easily achievable using the AnnAutomation.DeleteObject and DeleteObjects methods:

Documentation: AnnAutomation

Now that the additional functionalities are implemented, the final step is to recognize the new zones. Since the project already had to load the image and use the OcrEngine to AutoZone, I kept those in memory on the server so that everything is ready. I just need to pass the new XML data back to the server using PageMethods and the .NET AnnCodecs to load the new XML and get the zones out of it. Once I update the zones, I call the OcrDocument.Recognize method and then alert the user with the recognized text.

Overall this app was fun to write because it taught me a lot about client and server interaction. It was made much simpler by using the LEADTOOLS libraries since any one aspect of it (Annotations, OCR, Viewer) would have been extremely hard to implement without it. If I had more time I would look into porting the recognized text into an actual Outlook or Google contact.

Download the Project

The source code for this sample project can be downloaded from here.

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Linux OCR, Barcode and Format Conversion Batch Processor: 25 Projects in 25 Days

As part of the LEAD Technologies 25th anniversary, we are creating 25 projects in 25 days to celebrate LEAD’s depth of features and ease of use. Today’s project comes from Nathan.

What it Does

This C project will perform OCR, barcode recognition and file conversion using LEADTOOLS Version 19.

Features Used

Development Progress Journal

Hello, my name is Nathan and I am going to write a Linux application that combines OCR, barcode recognition, and file conversion into one batch processing application. It’s been quite a while since I’ve written a program in C so this should be fun!

Since I already have the LEADTOOLS SDK installed, I’m going to start with something simple to get my C gears turning. I’ll start by doing input verification, as I want to make sure the user uses the application properly and print out how to use it if they don’t.

That took a couple hours and I think I have input down pat. I’m going to store all of the options in a struct and then call functions that will do all the LEADTOOLS stuff from a header file if the flags are passed.

I’m going to go ahead and write a makefile that links all the libraries we’re going to need in this program so I don’t have to fiddle with compiling anymore and just type “make.”

Now I’m going to write a function that does file conversion. It’ll take a char * for source and target directories, intended format and then a struct to communicate the type with LEADTOOLS.

That only took about 45 minutes! I ran into some issues when opening directories, but it only took about 35 lines of code. That includes all the code we need to convert every file in our source directory, which is pretty amazing for C.

Now that I have that working, I’m going to write a function for barcode recognition.

That took about an hour and a half. Barcode recognition was a little trickier because I needed a couple helper functions to call from within. Even still, it wasn’t too bad and now my program can handle any barcode and it will write the data to a text file. And I can now do file conversion and barcode recognition from all the files by just passing both flags as command line arguments, that’s pretty sweet.

Now last but not least, I need to do OCR, which is a really complex thing to do!

That took about 3 hours since I’m not the most C-savvy person. Now I can OCR any image from the directory and output the text to a .txt file.

I need to do some code cleaning and commenting but this should only take about 20 minutes.

That wraps things up and brings me in at less than 8 hours. In one work day I was able to write a batch processing application that can do OCR, barcode recognition and file conversion, all in one. This is extremely useful for Linux users! Write a script to run this application and you can automate a lot of work.

In a future release, I’d probably like to separate some of my code into functions, do some multi-threading for performance, and allow for the int versions of the format constants or the common terms (tif, jpg, png, etc..) to be used.

Download the Project

The source code for this sample project can be downloaded from here.

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Scan to PDF Console: 25 Projects in 25 Days

As part of the LEAD Technologies 25th anniversary, we are creating 25 projects in 25 days to celebrate LEAD’s depth of features and ease of use. Today’s project comes from Faris.

What it Does

This C# console application will scan a page, extract text with OCR and save to PDF using LEADTOOLS Version 19.

Features Used

Development Progress Journal

Hello, my name is Faris and I’m going to create a console application which will scan a page from a scanner using TWAIN, recognize the text in the scanned page, and finally, save the recognized page as searchable PDF.

In this project, I will use LEADTOOLS Recognition Imaging SDK and program using .NET C# programming language.

The LEADTOOLS Recognition Imaging SDK provides me with the ability to scan from a TWAIN scanner, recognize the text in images using Optical Character Recognition (OCR) and save recognized images to document formats (PDF, DOCX, TXT).

It should be noted this application will recognize printed text in English alphabets, but not hand-written text. This can be customized to suit the programmer’s needs as our LEADTOOLS OCR engines support multiple languages and the Professional engine supports Intelligent Character Recognition (ICR).

First, I will start with a new Console Application in Visual Studio 2010. I will also add the needed SDK references for TWAIN, OCR and document writing functionalities.

I have now added the necessary code for starting up the TWAIN session, enumerating the scanners connected to the device and acquiring the image from the scanner. This took about 30 minutes of work.

Next came recognizing the acquired image. LEADTOOLS supports 3 different OCR engines: Advantage, Professional and Arabic. In my program, I will be using the Advantage engine.

The OCR engine must first be started, then the text in the image should be placed inside zones, and then the image will be ready for recognition. For zoning the image, I used the AutoZone method as I want to recognize the whole page, not a specific part of it. I found a really useful code example when searching LEADTOOLS online help documentation for the AutoZone method:

Documentation: IOcrPage

I have now finished adding the code for recognizing the scanned image. This took about an hour.

The next step is to save the recognized document as a searchable PDF. Luckily, the example I referenced earlier shows the code to achieve that. All I need to do is add the code for saving the recognized document in such a way to work with the previous step. The programmer can modify this part of the project to prompt the user to specify which file format the user wishes to save the output file as and also specify the output file’s name.

This part is now done and took about 30 minutes.

Finally, I’ll work on error handling and testing the code. I will test the application when 2 scanners are connected and when one scanner is connected. Because this is a console application, I will add multiple lines of code to write on the console the current operation being done to make the application informative for the user.

The final part is now done with about 2 hours of work. The total work time on the project, including developing, debugging and testing the program, was about 4 hours. Without the help of LEADTOOLS SDK, I wouldn’t have been able to finish the core functionality code within 2 hours, thus finishing the whole application in less than a single day’s work.

Download the Project

The source code for this sample project can be downloaded from here. To run the project, extract it to the C:\LEADTOOLS 19\Examples\DotNet\CS directory.

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