This paper is published in Volume 4, Issue 6, 2019
Area
Computer Science
Author
Nay Myo Aung
Org/Univ
Technological University, Mandalay, Myanmar, Myanmar
Pub. Date
27 June, 2019
Paper ID
V4I6-1142
Publisher
Keywords
Panoramic, Image stitching, Feature detection, Image matching, Blending, SIFT

Citationsacebook

IEEE
Nay Myo Aung. Panorama image processing system using Scale-Invariant Feature Transform (SIFT), International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARnD.com.

APA
Nay Myo Aung (2019). Panorama image processing system using Scale-Invariant Feature Transform (SIFT). International Journal of Advance Research, Ideas and Innovations in Technology, 4(6) www.IJARnD.com.

MLA
Nay Myo Aung. "Panorama image processing system using Scale-Invariant Feature Transform (SIFT)." International Journal of Advance Research, Ideas and Innovations in Technology 4.6 (2019). www.IJARnD.com.

Abstract

Image stitching is the process to generate one large panoramic image from collective relative image sequence without overlapping. Panoramic photo stitching is the process of combining multiple photographic images with overlapping fields of view to produce a panorama. The process to generate a panoramic view can be divided into three main components - image feature detection, image matching, and blending. Scale Invariant Feature Transform (SIFT) used to extract the features from the images and matching them which is a part of image registration. SIFT features are invariant to rotation, translation, image scaling and partially invariant to a 3D viewpoint, illumination changes and image noise. Image transformation is estimated using holography. Image blending technique is used to blend the images together to get a panoramic view. Main applications of panoramic view include creating a virtual environment for virtual reality, modeling the 3D environment using images acquired from the real world.