Volume 10 Issue 4 ( December )

Computer vision techniques for aligning and fusing images have long been employed to create smooth photographic mosaics. These methods have found applications in image stabilization features of camcorders, production of digital maps and satellite images through high-resolution photographic mosaics, and more. This paper introduces a novel method for generating composites from two or more images, with the ability to significantly reduce or eliminate white space when operating with a live connection. By leveraging algorithms such as Scale-Invariant Feature Transform (SIFT), the proposed method enables feature recognition and extraction from captured images, facilitating the removal of white space in live images. Additionally, this work presents a technique that merges live images with real-time camera input to complete missing elements by intelligently manipulating controlled elements in the images. The resulting approach offers a promising solution for real-time image fusion and the seamless integration of live camera feeds, enhancing the visual quality and completeness of the final composite.

Keywords: Computer vision techniques, Photographic mosaics, Image stitching algorithms, SIFT (Scale- Invariant Feature Transform), Real-time camera merging