Image Stitching Using Speeded Up Robust Features

Abstract

Images are an integral part of our daily lives. Image stitching is the process to generate one large panoramic image from collective relative image sequence without overlapping. Stitched images are used in applications such as Defence documentary photos, glob map, Inside or outs of the gallery, Space research images, sculpture art etc., the stitched images multi-node movies and other applications associated with modelling the 3D environment using images acquired from the real world. The existing method and algorithms are don’t have enough accuracy to make larger panoramic image. On-time collective of image sequence more easier compare to pre-collective images stitching. The better method for image stitching is SURF (Speeded Up Robust Features) algorithm. This robust method help out to stitches relative images much faster than SIFT (Scale Invariant Features Transform) algorithm. Most image processing techniques involve treating the image as a two-dimensional signal and applying standard signal processing techniques to it. Specifically, image stitching presents different stages to render two or more overlapping images into a both horizontal as well as vertical moves stitched image, from the detection of features to blending in a final panoramic image.
DOI: 10.17762/ijritcc2321-8169.150607