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-license: apache-2.0
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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.}
+}
+---
+
+## 📬 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.
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