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