Image Registration Techniques Based on the Scale Invariant Feature Transform

ABSTRACT

Image registration deals with establishing correspondences between images of the same scene or object. An image registration algorithm should handle the variations introduced by the imaging system capturing the scene. Scale Invariant Feature Transform (SIFT) is an image registration algorithm based on local features in an image. Compared to the previous registration algorithms, SIFT is more robust to variations caused by changes in size, illumination, rotation, and viewpoint of the images. Owing to its performance, the algorithm is widely studied, modified, and successfully applied in many image and video based applications, in the domains such as medicine, industry, and defense. This paper is an outcome of extensive study on the state-of-art image registration algorithms based on SIFT. Around 20 algorithms based on the SIFT algorithm is discussed. A classification is made based on the objective with which the basic algorithm is modified. A comparative study on the performance, methodology of each technique is presented along with their applicability to various image processing applications and domains.

KEYWORDS:

• Computer vision
• Feature extraction
• Image matching
• Image registration
• Pattern matching
• Pattern recognition
• SIFT

Additional information

Funding

This work was supported by the Council of Scientific and Industrial Research, the premier research and development organization in India, under the Senior Research Fellowship Scheme [grant number 09/1095/(0009)/2015-EMR-I].

Notes on contributors

K. Divya Lakshmi

K. Divya Lakshmi is currently doing her full-time research in image registration. She received her bachelor's degree in electronics and communication and master's degree in the domain of computer science engineering with specialization in knowledge engineering and computational linguistics. Her interests include programming, image processing, and machine learning.

E-mail: [email protected]

V. Vaithiyanathan

V. Vaithiyanathan is currently working as an associate dean of research and a professor in the School of Computing, SASTRA University. He is the principal investigator for several completed and ongoing government organization projects in the domain of computer vision and signal processing. His research interests include image processing and soft computing.

E-mail: [email protected]