README.md

metadata

license: apache-2.0

📷 SCIMD-6: Source Camera Identification — Mobile Devices Dataset

📂 Overview

SCIMD-6 is a carefully curated image dataset developed at Bapatla Engineering College to support research in source camera identification using images from mobile devices. The dataset contains 6315 RGB images, acquired from six different smartphones under diverse real-world conditions. The mobile devices used are Moto G64 5G (1006 image),Moto G85 5G(1037 images), Nothing A001(1036 images), Realme 8 Pro(1001 images), Redmi 14C 5G(1014 images),Xiaomi M2101K6P(1221 images). Total 6315 images.

📌 Note: Slight imbalance exists across classes but overall distribution is fairly uniform.

🌄 Image Characteristics

• 📐 Resolution: All images are resized to 224×224 pixels for compatibility with CNN architectures.
• 🌤️ Conditions: Captured in a variety of uncontrolled environments, including:
  • Indoor and outdoor
  • Sunny and rainy weather
  • Casual perspectives and variable lighting
• 🤳 Capture Style: Intentional lack of discipline in framing adds real-world complexity for model robustness testing.

📑 Included Files

• 📁 A zip file consisting of Motog64_5G/, Motog85_5G/, ..., Xiaomi_M2101K6P/: Folders containing 224×224 RGB images per mobile device.
• 📄 merged_common.csv: A metadata file containing EXIF information (Exchangeable Image File Format ) extracted from all images (e.g., Make, Model, ExposureTime, FocalLength).

🎯 Intended Use

This dataset is intended for tasks such as:

• 📸 Source Camera Identification (SCI)
• 🔬 Image Forensics and Provenance Analysis
• 🤖 Fine-grained Classification and Transfer Learning
• 🧠 Deep Learning Model Benchmarking in Forensic Settings 📚 Potential Applications of the Dataset This dataset, although primarily designed for source camera identification using mobile device images, supports a wide range of research directions and practical applications:

1. Source Camera Identification (SCI) • Classification of images based on the originating mobile device using intrinsic sensor characteristics. • Enables research in PRNU-based techniques and camera model/device fingerprinting.
2. Image Forensics and Metadata Consistency Analysis • Verification of metadata integrity using image content. • Detection of inconsistencies in EXIF fields such as shutter speed, ISO, focal length, and timestamp. • Applicable in detecting tampered or manipulated media.
3. Shutter Speed and ISO Estimation (Regression Tasks) • Pixel-to-metadata learning: predicting EXIF fields like ISO speed rating or exposure time directly from the image content. • Useful for modeling camera behavior and building metadata synthesis pipelines.
4. Image Quality Assessment (IQA) and Denoising • Training and benchmarking denoising models under real-world noise conditions (e.g., high ISO settings). • Correlation of EXIF parameters with perceptual quality for no-reference IQA research.
5. Environmental and Scene Classification • Scene-type inference (indoor/outdoor, sunny/cloudy, low-light conditions) based on visual content and EXIF cues. • Aids in tasks like environmental awareness, adaptive imaging, or low-light enhancement.
6. Image Provenance and Authorship Verification • Attribution of images to devices for media forensics and misinformation detection. • Combines device classification with temporal and spatial metadata for provenance tracing.
7. Training and Evaluation of Robust Vision Models • Offers real-world diversity in lighting, context, and device pipeline characteristics. • Supports robustness evaluation of CNNs, Vision Transformers, and vision-language models in uncontrolled environments.

The SCIMD-6 dataset is publicly available on multiple trusted platforms for broad accessibility and reproducibility.

📌 Citation

If you use this dataset in your research, please cite as: @dataset{chandramohan2025scimd6, author = {B. Chandra Mohan and Ch. Pavan Kumar and K. Sri Harsha and Ch. Nagaraju and Sandhyana T and Suvarna Lakshmi M}, title = {SCIMD-6: Source Camera Identification Mobile Devices Dataset}, year = {2025}, publisher = {Huggingface}, url = {https://huggingface.co/datasets/chandrabhuma/SCIMD-6}, note = {A benchmark dataset for source mobile camera identification with diversified conditions and EXIF metadata.} }

📬 Contact

For inquiries or academic collaborations: Dr. Chandra Mohan Bhuma
Department of Electronics & Communication Engineering
Bapatla Engineering College
✉️ chandrabhuma@gmail.com

🔒 License

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.