Compare OCR accuracy before and after applying our image processing routine.Discover how to apply thresholding, distance transforms, and morphological operations to clean up images.Learn how basic image processing can dramatically improve the accuracy of Tesseract OCR.You can then use this example as a starting point for cleaning up your images with basic image processing for OCR. This tutorial will provide you with such an example. I will publish a blog with a real-time application of Text OCR.Looking for the source code to this post? Jump Right To The Downloads Section Improving OCR Results with Basic Image ProcessingĮxactly which image processing algorithms or techniques you utilize is heavily dependent on your exact situation, project requirements, and input images however, with that said, it’s still important to gain experience applying image processing to clean up images before OCR’ing them. Using (var engine = (tessDataPath, "eng"))Įngine.Run(img, out result, out textLocations, out componentTexts, out confidences, ) String tessDataPath = DownloadAndExtractLanguagePack() string imagePath = + img = Cv2.ImRead(imagePath) Without much discussion, I will show the code and the result which is similar to what we got with the above library. The OpenCV library has an OCRTesseract class which gives more information other than text such as the location of text on the image and confidence score which can be useful. The method GetText will extract the text from the image.Here we are using Tesseract provided image library to load the image. The engine has Process method which takes Image as an input.First, need to initialise the Tesseract engine with the training language module.Using (var img = Pix.LoadFromFile(imagePath)) Using (var engine = new TesseractEngine(tessDataFolder, "eng", EngineMode.Default)) Here is the code and result: string imagePath = + tessDataFolder = DownloadAndExtractLanguagePack() Here is the demo image that I will be using to extract the text. Var extractedDir = Directory.EnumerateDirectories().FirstOrDefault(x => (x.Contains("tessdata"))) ĭirectory.Move(extractedDir, tessDataFolder) ZipFile.ExtractToDirectory(zipFileName, ) If (string.IsNullOrWhiteSpace(tessDataFolder)) String tessDataFolder = + " essdata" Ĭlient.DownloadFile(langPackPath, zipFileName) String zipFileName = + " essdata.zip" Below is the code which will download and extract the language pack for you: private static string DownloadAndExtractLanguagePack() Demo using Tesseract libraryįor the Tesseract engine to load and extract information from the image, we need language pack. Like we did in the previous blogs, please install the OpenCVSharp and Tesseract library using Nuget. NET core for now, but as per the community, there is an implementation in progress. NET standard framework since Tesseract does not support. Let start with new C# console project, this time choose a. The Open CV also comes with an inbuilt wrapper for Tesseract, and so I will showcase the usage of both the library. NET there is a wrapper developed by “Charles Weld” and is maintained by the open source community. Here is the actual code repo of the project: In 2005 Tesseract was open sourced by HP. Tesseract was originally developed at Hewlett-Packard Laboratories Bristol and at Hewlett-Packard Co, Greeley Colorado between 19, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. Tesseract is one of the populated libraries, which contains OCR engine and supports more than 100 languages and has code in place so that it can be easily trained on another language OCR is a mechanism to convert images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo on an image.
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