Abstract: Image matching and recognition are the crux of computer vision and have a major part to play in everyday lives. From industrial robots to surveillance cameras, from autonomous vehicles to medical imaging and from missile guidance to space exploration vehicles computer vision and hence image matching is embedded in our lives. This communication presents a comparative study on the prevalent matching algorithms, addressing their restrictions and providing a criterion to define the level of efficiency likely to be expected from an algorithm. The study includes the feature detection and matching techniques used by these prevalent algorithms to allow a deeper insight. The chief aim of the study is to deliver a source of comprehensive reference for the researchers involved in image matching, regardless of specific applications.

Usman Muhammad Babri, Munim Tanvir and Khurram Khurshid, “Feature Based Correspondence: A Comparative Study on Image Matching Algorithms” International Journal of Advanced Computer Science and Applications(IJACSA), 7(3), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070329

@article{Babri2016,
title = {Feature Based Correspondence: A Comparative Study on Image Matching Algorithms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070329},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070329},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Usman Muhammad Babri and Munim Tanvir and Khurram Khurshid}
}