Umi-OCR - A free OCR text recognition tool that supports screenshots and batch image layout and parsing.

What is Umi-OCR?

Umi-OCR is a free and open-source offline OCR text recognition software. No internet connection is required; it's ready to use immediately after extraction. It supports text recognition from screenshots, batch images, and scanned PDFs, and can recognize mathematical formulas and QR codes. It can generate two-layer searchable PDFs. It has a built-in multilingual recognition library, supports multilingual interface switching, and provides command-line and HTTP API access. Its plug-in design allows for expansion with more features, such as importing different language recognition libraries.

Main functions of Umi-OCR

• Screenshot OCRIt can quickly recognize text in screenshots, supports layout parsing, and outputs text content in the correct order.
• Batch Image OCRIt supports batch recognition of text in images, and allows you to set ignore areas to exclude interfering content such as screenshot watermarks.
• PDF Recognition and ProcessingIt can extract text from scanned PDFs and convert PDFs into two-layer searchable PDFs for easy editing and searching later.
• QR code recognition and generationIt supports scanning QR codes to obtain information, and also supports generating QR code images.
• Formula recognitionIt has mathematical formula recognition capabilities, which can help users quickly extract and edit formula content.
• Multilingual supportIt has built-in multilingual recognition libraries, supports text recognition in multiple languages, and the interface also supports multilingual switching.
• Flexible InvocationIt supports external calling methods such as command line and HTTP interface, making it easy to integrate with other software or tools.

Umi-OCR's technical principle

• Image preprocessingThe input image is processed by grayscale conversion, binarization, and noise reduction to improve text clarity, reduce background interference, and provide a clearer image for subsequent text detection and recognition.
• Text detectionIt detects and segments text regions in images using algorithms such as Convolutional Neural Networks (CNNs). It can recognize text regions with different fonts, sizes, and arrangements.
• Text recognitionThe system extracts features from the detected text regions, uses deep learning models (such as PaddleOCR-based models) for classification and recognition, and converts the text images into computer-readable text information.
• Post-processingThe system performs correction and formatting operations on the recognition results, such as merging text in the same paragraph, processing vertical text, and optimizing the final output format.

Umi-OCR project address

• Github repository:https://github.com/hiroi-sora/Umi-OCR

Application scenarios of Umi-OCR

• Document digitizationUmi-OCR can convert paper documents, books, contracts, etc. into editable electronic text, improving the efficiency of document storage and retrieval.
• Automated data entryIn enterprises, Umi-OCR can be used to automatically extract data from documents such as invoices, reports, and certificates, reducing manual input errors and improving work efficiency.
• EducationTeachers can use Umi-OCR to convert images and text in textbooks or test papers into text format, making it easier for students to read and answer questions.
• Software Interface Text Extraction: Suitable for software that cannot copy text, such as text extraction in games and image editors.
• Machine learning data preprocessingIn Natural Language Processing (NLP) tasks, Umi-OCR can convert scanned text into training data.