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In this tutorial, we explore how to use computer vision to detect text in images using the Iron OCR library in C. We begin by setting up a C console application in Visual Studio, ensuring the Iron OCR and Iron Doomu Vision packages are installed via the NuGet Package Manager. First, we import the Iron OCR library to access OCR functionalities and create an instance of the Iron Tesa class for OCR operations. We open an input image file and define an OCR input object, using computer vision to detect text regions. The read method of the Iron Tesa object is then used to perform OCR, storing results in a variable for display.
The tutorial also covers using the crop rectangle class to focus on identified text regions, applying a red stamp for visual inspection, and further processing with the read method. Additionally, we demonstrate detecting multiple text regions, dividing input into separate images, and using the get text regions method for comprehensive text extraction. With the right settings and input files, Iron OCR combined with computer vision can become a potent tool for text detection. The tutorial concludes by encouraging viewers to download a trial version of Iron OCR for further exploration.
Further Reading: How to use Computer Vision to Find Text