## Creating See-Around Scenes using Panorama Stitching

### Saja Alferidah, Nora Alkhaldi

DOI: http://dx.doi.org/10.15439/2019F282

Citation: Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 18, pages 293–301 (2019)

Abstract. Image stitching refers to the process of combining multiple images of the same scene to produce a single high-resolution image, known as panorama stitching. The aim of this paper is to produce a high-quality stitched panorama image with less computation time. This is achieved by proposing four combinations of algorithms. First combination includes FAST corner detector, Brute Force K-Nearest Neighbor (KNN) and Random Sample Consensus (RANSAC). Second combination includes FAST, Brute Force (KNN) and Progressive Sample Consensus (PROSAC). Third combination includes ORB, Brute Force (KNN) and RANSAC. Fourth combination contains ORB, Brute Force (KNN) and PROSAC. Next, each combination involves a calculation of Transformation Matrix. The results demonstrated that the fourth combination produced a panoramic image with the highest performance and better quality compared to other combinations. The processing time is reduced by 67\% for the third combination and by 68\% for the fourth combination compared to stat-of-the-art.

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