Giving access to line-level handwritten English text images and transcriptions categorized for text recognition and writer identification. All image instances are resized to an uniform height of 128 pixels to support standardized input for neural network architectures.
Use Cases
- Train handwritten text recognition (HTR) models using the 'image' column and corresponding transcriptions.
- Develop writer identification systems by analyzing handwriting styles within the line-level images.
- Benchmark optical character recognition (OCR) accuracy on English handwriting samples.
Strengths
- Features line-level image segments extracted from the IAM Handwriting Database.
- All images are normalized to a fixed height of 128 pixels.
- Includes an 'image' column containing handwritten English text samples.