Antoni Wibowo

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About

Antoni Wibowo is a researcher whose work sits at the intersection of computer vision, optical character recognition (OCR), and digital image preprocessing. His most-cited paper, “The Effectiveness of Image Preprocessing on Digital Handwritten Scripts Recognition with The Implementation of OCR Tesseract” (2021), has garnered 22 citations and addresses a critical bottleneck in automated text extraction: the challenge of recognizing handwritten scripts. By systematically evaluating preprocessing techniques—such as noise reduction, binarization, and skew correction—Wibowo demonstrated how these steps significantly boost the accuracy of Tesseract OCR, a widely used open-source engine. This contribution is particularly valuable for digitizing historical manuscripts, personal notes, and forms where handwriting varies widely. Beyond this flagship study, his broader research explores how robust preprocessing pipelines can bridge the gap between raw image data and reliable machine-readable text, a foundational need in AI-driven document analysis. Wibowo’s work not only advances practical OCR applications but also provides a reproducible framework for researchers tackling similar recognition tasks. His findings underscore that preprocessing is not merely a preliminary step but a decisive factor in achieving high-performance character recognition, making his insights essential for students and engineers working on digital handwriting systems.