VB.NET code snippet like this for ByteScout PDF Suite works best when you need to quickly implement ocr with fast dataset with pdf extractor sdk in your VB.NET application. If you want to know how it works, then this VB.NET sample code should be copied and pasted into your application’s code editor. Then just compile and run it. Updated and detailed documentation and tutorials are available along with installed ByteScout PDF Suite if you’d like to learn more about the topic and the details of the API.
On our website you may get trial version of ByteScout PDF Suite for free. Source code samples are included to help you with your VB.NET application.
Imports Bytescout.PDFExtractor ' This example demonstrates the use of Optical Character Recognition (OCR) to extract text ' from scanned PDF documents and raster images. ' To make OCR work you should add the following references to your project: ' "Bytescout.PDFExtractor.dll", "Bytescout.PDFExtractor.OCRExtension.dll". Class Program Friend Shared Sub Main(args As String()) ' Create Bytescout.PDFExtractor.TextExtractor instance Dim extractor As New TextExtractor() extractor.RegistrationName = "demo" extractor.RegistrationKey = "demo" ' Load sample PDF document extractor.LoadDocumentFromFile("sample_ocr.pdf") ' Enable Optical Character Recognition (OCR) ' in .Auto mode (SDK automatically checks if needs to use OCR or not) extractor.OCRMode = OCRMode.Auto ' Set the location of OCR language data files extractor.OCRLanguageDataFolder = "c:\Program Files\Bytescout PDF Extractor SDK\ocrdata_fast" ' Set OCR language extractor.OCRLanguage = "eng" ' "eng" for english, "deu" for German, "fra" for French, "spa" for Spanish etc - according to files in "ocrdata" folder ' Find more language files at https://github.com/bytescout/ocrdata/tree/master/ocrdata_fast ' Set PDF document rendering resolution extractor.OCRResolution = 300 ' You can also apply various preprocessing filters ' to improve the recognition on low-quality scans. ' Automatically deskew skewed scans 'extractor.OCRImagePreprocessingFilters.AddDeskew() ' Remove vertical or horizontal lines (sometimes helps to avoid OCR engine's page segmentation errors) 'extractor.OCRImagePreprocessingFilters.AddVerticalLinesRemover() 'extractor.OCRImagePreprocessingFilters.AddHorizontalLinesRemover() ' Repair broken letters 'extractor.OCRImagePreprocessingFilters.AddDilate() ' Remove noise 'extractor.OCRImagePreprocessingFilters.AddMedian() ' Apply Gamma Correction 'extractor.OCRImagePreprocessingFilters.AddGammaCorrection() ' Add Contrast ' extractor.OCRImagePreprocessingFilters.AddContrast(20) ' (!) You can use new OCRAnalyzer class to find an optimal set of image preprocessing ' filters for your specific document. ' See "OCR Analyser" example. ' Save extracted text to file extractor.SaveTextToFile("output.txt") ' Cleanup extractor.Dispose() ' Open output file in default associated application System.Diagnostics.Process.Start("output.txt") End Sub End Class