Understanding SIFT Algorithm and its uses

Author(s):

Akshat Poi , Don Bosco College of Engineering; Samantha Cardoso, Don Bosco College of Engineering; Sahil Khorjuvenkar, Don Bosco College of Engineering; Sairaaj Shirodkar , Don Bosco College of Engineering; Vaibhav Naik, Don Bosco College of Engineering

Keywords:

Difference of Gaussian, extrema detection, key point localization, SIFT algorithm

Abstract:

The Scale Invariant Feature Transform [1] (SIFT) is an algorithm in image processing to detect and describe local features in an image. It takes an image and transforms it into a collection of local feature vectors. Each of these vectors is supposed to be different and distinctive and also invariant to scaling, rotation or translation of the image. In real-time applications these features can be can be used to find distinctive objects in different images and the transform can be extended to match certain areas in images. This document describes the basic implementation of the SIFT algorithm in various applications and also highlights a potential direction for future research.

Other Details:

Manuscript Id	:	IJSTEV2I10141
Published in	:	Volume : 2, Issue : 10
Publication Date	:	01/05/2016
Page(s)	:	556-560

Download Article