OCR stands for Optical Character Recognition. It is a technology that allows for the conversion of scanned documents, images, or PDFs containing text into editable and searchable digital documents. OCR software uses optical recognition algorithms to identify and extract the text from an image or scanned document and then convert it into a digital format that can be edited or searched using a computer. This technology has a wide range of applications, including digitizing paper documents, extracting text from images for translation or analysis, and enabling the search and retrieval of text within digital documents.
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Best Ocr Apps
There are many OCR apps available that you can use to convert images or scanned documents into editable text. Some of the best OCR apps include:
- Adobe Acrobat Pro DC – This app offers advanced OCR capabilities and allows you to convert scanned documents and images into editable PDFs or Word documents.
- ABBYY FineReader – This app is known for its high accuracy and supports over 200 languages. It also has a range of features including the ability to recognize text in tables and convert scanned documents into editable formats.
- Nuance OmniPage – This app offers a wide range of OCR features, including the ability to convert scanned documents into a variety of editable formats, support for over 120 languages, and the ability to recognize text in images.
- Tesseract OCR – This is an open-source OCR engine that is highly accurate and supports over 100 languages. It is available for use on Windows, Linux, and MacOS.
- Smallpdf OCR – This is a cloud-based OCR app that allows you to convert images or scanned documents into editable formats. It is easy to use and supports over 70 languages.
These are just a few examples of OCR apps that are available. It’s worth considering your specific needs and doing some research to find the app that is the best fit for you.
How Ocr Works?
OCR (Optical Character Recognition) technology works by analyzing the pixels in an image or scanned document and attempting to recognize the characters present. Here is a general overview of the steps involved in the OCR process:
- Preprocessing: The image or scanned document is preprocessed to prepare it for OCR. This may involve removing noise or adjusting the contrast to improve the quality of the image.
- Segmentation: The image is divided into small segments, each of which represents a single character.
- Feature Extraction: The OCR software extracts features from each segment that can be used to identify the character. These features might include the shape of the character, the relative position of different parts of the character, or the patterns of pixels within the character.
- Classification: The OCR software compares the features of each character segment to a set of reference characters and assigns a label to each character based on the best match.
- Post-Processing: The OCR software may perform additional processing on the recognized text to correct errors or improve the formatting of the output.
- Output: The recognized text is output in a digital format that can be edited or searched using a computer.
OCR technology has become quite sophisticated and can recognize text in a wide range of fonts and languages. However, the accuracy of OCR can vary depending on the quality of the input image and the complexity of the text.