OCR (Optical Character Recognition) technology can be greatly improved by removing background noise from images. Background noise, such as texture, patterns, and color variations, can interfere with OCR algorithms, leading to inaccurate results. In this guide, we will explore various methods for removing background noise from images to enhance the accuracy of OCR. Whether it’s utilizing image processing libraries, machine learning models, or specialized software, the goal is to ensure that the text within images can be accurately extracted and recognized by OCR systems. By implementing these techniques, the overall quality and reliability of OCR processes can be significantly enhanced.