6. Conclusions and future scope - radhikahorti/Embedding-Synthetic-Pattern GitHub Wiki

6.1 Conclusion

The technique provides a GUI for interactive picture modification and provides a variety of options for embedding artificial patterns into RAW photographs.Users select insertion methods—simple positioning, contrast matching, or preserving desired image features—to embed patterns.The method creates modified RAW photos and handles the embedding. Heatmaps are created for visual comparison by local statistic measures, which evaluate intensity differences, mean luminance, contrast, and histogram. Using ARGUS APIs, both RAW photos are converted to JPEG. To aid in comprehensive examination and assessment of the similarities between the original and changed pictures, the method also computes SSIM scores for global statistics comparison. This allows for well-informed decision-making in image processing jobs.

6.2 Future scope

Exciting prospects are ahead for artificial pattern embedding onto pictures. Advances might consist of improving customisation, investigating flexible embedding techniques that modify patterns in real-time according to user choices or the content of images.We can also create AI systems that can recognize the best embedding locations by taking into account the properties of the images in order to integrate them seamlessly.It may also facilitate cross-modal information fusion, extend embedding beyond visual patterns to encompass a variety of data kinds, such as audio, text, or 3D objects.

We can design user-friendly graphical user interfaces (GUIs) or augmented reality (AR) interfaces that enable users to interactively see and control embedded patterns in real-world situations.

Both quantitative and qualitative assessment measures should be developed in order to gain a better knowledge of the impacts of pattern embedding on pictures, going beyond SSIM. they may help in the integration of apps in several domains such as augmented reality, data concealing, healthcare (medical imaging markers), and authentication.

New frontiers across industries and user experiences will be opened by future developments in synthetic pattern embedding, which have the potential to revolutionize information integration, content augmentation, and visual modification.