--- title: Maximizing Text Recognition Accuracy with Image Transformers in Spark OCR description: This webinar describes real-world OCR use cases, common accuracy issues they bring, and how to use image transformers in Spark OCR in order to resolve them at scale. 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A primary method of maximizing accuracy is using a set of pre-built image pre-processing transformers - for noise reduction, skew correction, object removal, automated scaling, erosion, binarization, and dilation. These transformers can be combined into OCR pipelines that effectively resolve common 'document noise' issues that reduce OCR accuracy. This webinar describes real-world OCR use cases, common accuracy issues they bring, and how to use image transformers in Spark OCR in order to resolve them at scale. Example Python code will be shared using executable notebooks that will be made publicly available. ###### About the speaker Mykola Melnyk is a senior Scala, Python, and Spark software engineer with 15 years of industry experience. He has led teams and projects building machine learning and big data solutions in a variety of industries - and is currently the lead developer of the Spark OCR library at John Snow Labs. ### Recent blog posts ### Get to work Need NLP Software? 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