ByteScout simple and easy to understand tutorials are planned to describe the code for both VB.NET beginners and advanced programmers. ByteScout Premium Suite is the bundle that includes twelve SDK products from ByteScout including tools and components for PDF, barcodes, spreadsheets, screen video recording. It can be applied to convert scanned pdf to json with pdf extractor sdk using VB.NET.
The SDK samples given below describe how to quickly make your application do convert scanned pdf to json with pdf extractor sdk in VB.NET with the help of ByteScout Premium Suite. Follow the instructions from scratch to work and copy the VB.NET code. Check VB.NET sample code samples to see if they respond to your needs and requirements for the project.
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Imports Bytescout.PDFExtractor ' This example demonstrates the use of Optical Character Recognition (OCR) to extract text into json ' 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.JSONExtractor instance Dim extractor As New JSONExtractor() 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" ' 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 ' 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.SaveJSONToFile("output.json") ' Cleanup extractor.Dispose() ' Open output file in default associated application System.Diagnostics.Process.Start("output.json") End Sub End Class