README.md

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license: apache-2.0
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# 📷 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.}
}
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## 📬 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.