Datasets:
Modalities:
Image
Formats:
imagefolder
Size:
1K - 10K
Tags:
dataset
signature-verification
handwritten-signature
offline-signature-verification
biometric-authentication
computer-vision
License:
| license: mit | |
| tags: | |
| - dataset | |
| - signature-verification | |
| - handwritten-signature | |
| - offline-signature-verification | |
| - biometric-authentication | |
| - computer-vision | |
| - document-ai | |
| pretty_name: Multilingual Signature Verification Dataset | |
| size_categories: | |
| - 1K<n<10K | |
| language: | |
| - en | |
| - hi | |
| - bn | |
| task_categories: | |
| - image-classification | |
| - image-feature-extraction | |
| # Multilingual Signature Verification Dataset | |
| ## Dataset Summary | |
| The **Multilingual Signature Verification Dataset** is a curated collection of handwritten signatures designed for **offline signature verification** and related computer vision tasks. | |
| The dataset contains more than **7,000 signature images** spanning three major writing systems: | |
| - **Hindi** | |
| - **Bengali** | |
| - **English** | |
| The English portion includes samples from the well-known **CEDAR Signature Dataset**, while additional Hindi and Bengali signatures have been curated to support multilingual signature verification research. | |
| The dataset has been preprocessed and organized into ready-to-use **train**,**test** and **valid** splits for machine learning workflows. | |
| --- | |
| # Supported Tasks | |
| This dataset can be used for: | |
| - Offline Signature Verification | |
| - Signature Classification | |
| - Signature Recognition | |
| - Siamese Network Training | |
| - Contrastive Learning | |
| - Metric Learning | |
| - Image Embedding Models | |
| - Document AI Research | |
| - Handwritten Biometrics | |
| --- | |
| # Dataset Structure | |
| ``` | |
| dataset/ | |
| ├── train/ | |
| │ ├── person_0001/ | |
| │ ├── person_0002/ | |
| │ ├── ... | |
| │ | |
| └── test/ | |
| ├── person_0005/ | |
| ├── person_0021/ | |
| ├── ... | |
| ``` | |
| Each class corresponds to a unique signer identity. | |
| --- | |
| # Dataset Statistics | |
| | Property | Value | | |
| |----------|-------| | |
| | Total Samples | 7,000+ | | |
| | Languages | English, Hindi, Bengali | | |
| | Data Type | Offline handwritten signatures | | |
| | Train/Test Split | Yes | | |
| | Image Format | PNG/JPG (depending on uploaded files) | | |
| | Task | Signature Verification | | |
| --- | |
| # Languages Included | |
| ## English | |
| The English subset contains signatures derived from the **CEDAR Signature Dataset**, one of the most widely used benchmark datasets for offline signature verification research. | |
| ## Hindi | |
| Contains handwritten signatures written in the Devanagari script. | |
| ## Bengali | |
| Contains handwritten signatures written in the Bengali script. | |
| The multilingual composition enables research on language-independent and script-independent signature verification models. | |
| --- | |
| # Loading the Dataset | |
| Using the 🤗 Datasets library: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("rakshitdabral/Signature-Verification-Dataset") | |
| ``` | |
| Example: | |
| ```python | |
| train = dataset["train"] | |
| test = dataset["test"] | |
| print(train[0]) | |
| ``` | |
| --- | |
| # Example Training Applications | |
| This dataset is suitable for training: | |
| - ResNet | |
| - ConvNeXt | |
| - Vision Transformer (ViT) | |
| - EfficientNet | |
| - MobileNet | |
| - Siamese Networks | |
| - Triplet Networks | |
| - ArcFace-based Models | |
| - Contrastive Learning Pipelines | |
| --- | |
| # Recommended Evaluation Metrics | |
| - Accuracy | |
| - Precision | |
| - Recall | |
| - F1 Score | |
| - ROC-AUC | |
| - Equal Error Rate (EER) | |
| - False Acceptance Rate (FAR) | |
| - False Rejection Rate (FRR) | |
| --- | |
| # Intended Use | |
| This dataset is intended for: | |
| - Academic research | |
| - Signature verification systems | |
| - Identity verification research | |
| - Document processing | |
| - Machine learning benchmarking | |
| - Deep learning research | |
| - Educational purposes | |
| --- | |
| # Limitations | |
| - The dataset focuses on **offline handwritten signatures** only. | |
| - It is not intended for online signature dynamics (pressure, speed, stroke order). | |
| - Performance may vary across scripts depending on model architecture and training strategy. | |
| --- | |
| # Citation | |
| If you use this dataset in your research, please cite this repository. | |
| ```bibtex | |
| @dataset{signature_verification_dataset, | |
| title={Multilingual Signature Verification Dataset}, | |
| author={Rakshit Dabral}, | |
| year={2026}, | |
| publisher={Hugging Face}, | |
| url={https://huggingface.co/datasets/rakshitdabral/Signature-Verification-Dataset} | |
| } | |
| ``` | |
| --- | |
| # License | |
| This dataset is released under the **MIT License**. | |
| Please ensure compliance with the licensing terms of any original source datasets (such as the CEDAR Signature Dataset) when using or redistributing derived data. | |
| --- | |
| # Acknowledgements | |
| - CEDAR Signature Dataset | |
| - Hugging Face Datasets | |
| - Open-source computer vision community | |
| --- | |
| # Contact | |
| For questions, issues, or contributions, please open an issue on the Hugging Face repository or contact the dataset maintainer. |