Logo
/
Sign in
Product Logo
Aspose.OMR for .NETAspose

Create machine-readable answer sheets, surveys, ballots, questionnaires, and other OMR forms, and read optical marks from scanned images and photos in a few lines of .NET code.

Vendor

Vendor

Aspose

Screenshot_16-2-2026_152140_products.aspose.com.jpeg
Product details

Aspose.OMR for .NET is a powerful Optical Mark Recognition API that enables developers to create, customize, and recognize machine-readable forms such as answer sheets, surveys, tests, ballots, and questionnaires. It transforms scanned images or photos into structured data with near 100% accuracy, using only standard office equipment like copiers or smartphone cameras. With its markup-based or programmatic form design system, users can generate sophisticated OMR templates without needing external design tools. The library supports cross-platform operation on any environment running .NET Framework 4.0 or later, including Windows, Linux, cloud platforms, and containerized deployments. Aspose.OMR for .NET includes tools for generating printable forms, recognizing filled images, extracting results as CSV, JSON, or XML, and personalizing forms with QR codes, barcodes, respondent information, and branding elements. Designed for scalability, it enables processing hundreds of forms per minute and supports multi-page formats, localization, advanced recognition tuning, and a rich set of layout elements.

Features

Form Creation & Template Design

  • Create machine-readable OMR forms with any layout or complexity.
  • Build forms via plain text markup, JSON, or programmatically.
  • Supports 20+ layout and content elements for flexible form creation.
  • Generate answer sheets, ballots, surveys, application forms, assessments, and custom templates.
  • Add barcodes, QR codes, logos, corporate footers, photos, identifiers, and personalized fields.
  • Supports all paper sizes, including non-standard formats. Form Rendering & Output
  • Render printable OMR forms to PDF.
  • Easily integrate form generation into .NET applications using only a few lines of code.
  • No external or specialized OMR hardware required. Form Recognition
  • Recognize hand-filled forms from scans (JPEG, PNG, TIFF, GIF, BMP), PDFs, or smartphone photos.
  • Accepts lightly marked responses, pen/pencil/marker input, and varied mark shapes and sizes.
  • Apply recognition templates for automated processing.
  • Export recognition results to CSV, JSON, or XML for analytics or database import.
  • Batch-processing support: process entire folders with a single command.
  • Multi-page recognition for complex or lengthy forms. Personalization & Localization
  • Multi-language support, including:
  • English, French, Cyrillic languages, Arabic, Persian, Hebrew, Urdu, Bengali.
  • Left‑to‑right and right‑to‑left text direction, native numbering systems, and global script support. Deployment & Platform Independence
  • Works on any platform supporting .NET Framework 4.0+.
  • Supports Windows, Linux, Azure, AWS, Docker, and on‑premise servers.
  • Distributed as a lightweight NuGet package or downloadable package. Advanced Features
  • Accuracy tuning for challenging conditions (lighting, noise, low-resolution images).
  • Fully automated markup generation from interactive online form designer.
  • Generate OMR forms programmatically with just 3 lines of code.
  • Create an optical mark reader application in as few as 5 lines of code.

Benefits

  • No specialized equipment: Use scanners or smartphone cameras instead of expensive OMR hardware.
  • Fast and scalable: Processes hundreds of forms per minute with high accuracy.
  • Easy to learn: Only basic C# knowledge needed; forms can be created in minutes.
  • Highly customizable: Personalize forms with branding, identification fields, and machine-readable codes.
  • Global readiness: Create multilingual forms that support international respondents.
  • End-to-end automation: From form generation to recognition and data export, all within .NET.
  • Cost-effective: Eliminates manual data entry and reduces human error.