Arabic OCR Images Data – Images with Transcription

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Project Overview:

Objective

To build a dataset of Arabic OCR Images Data, we focused on gathering OCR images and their corresponding transcriptions in Arabic. This dataset is intended for training and evaluating OCR and text recognition systems capable of accurately converting scanned or handwritten Arabic text into digital text.

Scope

Collect a diverse set of images containing Arabic text, transcribe the text into digital format, and ensure high-quality image-text pairs for OCR model training.

Sources

Image Collections: Obtain a variety of image sources containing Arabic text, including scanned documents, handwritten notes, books, historical documents, and public domain text.
Crowdsourcing: Employ crowdsourcing platforms to collect handwritten text samples and transcriptions.

Data Collection Metrics

Total OCR Images: 50,000 images
Handwritten Samples: 10,000 samples
Transcriptions: Corresponding digital transcriptions for all images

Annotation Process

Stages

Image Selection: Curate a diverse set of images containing Arabic text, ensuring various fonts, styles, and writing types (script, cursive, calligraphy, etc.).
OCR and Transcription: Use OCR software to extract text from images automatically. Review and correct the OCR output to ensure accuracy and completeness of transcriptions.
Handwritten Samples: Collect handwritten samples through crowdsourcing platforms, ensuring a wide range of handwriting styles.
Transcription Validation: Validate the quality of transcriptions through manual review and verification.

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

Transcription Verification: Implement a validation process involving human reviewers who are fluent in Arabic to verify the correctness of transcriptions and OCR output.
Privacy Compliance: Ensure compliance with privacy regulations, especially when handling potentially sensitive handwritten documents.
Data Security: Implement data security measures to protect any personal or 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

The Arabic OCR Images Data with Transcriptions dataset is an essential resource for OCR and text recognition research and development in the Arabic language. It includes diverse images and accurate transcriptions. Furthermore, it adheres to privacy and security standards. As a result, it enables the training and evaluation of OCR models for Arabic text.

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