Spanish (Mexico) OCR Images Data – Images with Transcription

Project Overview:

Objective

As a premier provider of data collection and annotation services, we successfully executed a project that aimed to create a robust dataset of OCR (Optical Character Recognition) images paired with accurate transcriptions in Mexican Spanish. This dataset is tailored for enhancing machine learning models dedicated to OCR and text recognition technologies.

Scope

Our project entailed the collection of a vast and varied compilation of images embedded with Spanish text, which we meticulously transcribed into digital formats. We are proud to have contributed to the development of OCR models with this dataset, ensuring a range of image-text pairs of the highest quality.

Spanish (Mexico) OCR Images Data – Images with Transcription
Spanish (Mexico) OCR Images Data – Images with Transcription
Road Sign Recognition

Sources

  • Image Collections: Obtained a variety of image sources containing Spanish text, including scanned documents, handwritten notes, books, and public domain text.
  • Crowdsourcing: Employed crowdsourcing platforms to collect handwritten text samples and transcriptions.
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Road Sign Recognition

Data Collection Metrics

  • Total OCR Images Collected: 50,000 images
  • Handwritten Samples Collected: 10,000 samples
  • Random Volume Addition: Total Data Points Collected: 120,000; Total Data Points Annotated: 110,000

Annotation Process

Stages

  1. Image Curation: We gathered a comprehensive assortment of images containing Spanish text, highlighting a diversity of fonts, styles, and writing types.
  2. OCR and Transcription: Our advanced OCR technology facilitated the initial text extraction, followed by a meticulous review process to guarantee transcription precision.
  3. Handwritten Sample Acquisition: Utilizing crowdsourcing platforms, we amassed a broad spectrum of handwritten text samples.
  4. Transcription Validation: A rigorous validation protocol was employed to confirm the transcription quality.

Annotation Metrics

  • OCR Images with Transcriptions: 50,000 pairs
  • Handwritten Samples: 10,000 samples
  • Transcription Validation Cases: 5,000 (randomly selected for validation)

Quality Assurance

Stages

With an unwavering commitment to quality, our team ensured that each transcription met our high standards of accuracy. Our process was designed not only to respect privacy laws but also to uphold data security for sensitive information.

QA Metrics

  • Transcription Validation Accuracy: Ensure a high level of accuracy (e.g., 99%+) in transcription validation.
  • Privacy Audits: Ongoing to ensure compliance

Conclusion

Our successful completion of the Spanish (Mexico) OCR Images Data with Transcriptions project stands as a testament to our expertise in data collection and annotation for machine learning applications. We are confident that our dataset will significantly contribute to the advancements in OCR and text recognition research, specifically catering to the nuances of the Mexican Spanish language.

quality dataset

Quality Data Creation

Guaranteed TAT​

Guaranteed TAT

ISO 9001:2015, ISO/IEC 27001:2013 Certified​

ISO 9001:2015, ISO/IEC 27001:2013 Certified

HIPAA Compliance​

HIPAA Compliance

GDPR Compliance​

GDPR Compliance

Compliance and Security​

Compliance and Security

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