1. Comparison of image matching techniques
Authors : Jayanthi N., Indu S.
Pages : 396-401
DOI : http://dx.doi.org/10.21172/1.73.552
Keywords : Feature Detection, Blob Detection, Template Matching, SIFT, SURF Abstract :In the past few centuries, with the rise in robotics studies and experimenting, the use of high quality camera sensors with high zooming capabilities has increased manifold. Aiming to provide vision capabilities alike human beings, cameras generate a wide variety of images which are required to be examined and assessed for further research and to generate meaningful solutions for a given problem. In this paper, an insight has been provided on how various image recognition and tracking algorithms perform on various datasets. A wide range of data sets have been chosen, ranging from hand gestures to shapes and objects to handwritten manuscript text, etc. The algorithms whose performance is being analysed are namely Blob detection method, Template matching algorithm and S.U.R.F Algorithm. We have compared these image matching algorithms on the basis of various measures such as accuracy, processing speed, flexibility to use for various data sets, invariance to rotation, scale and illumination, etc.
Citing this Journal Article :Jayanthi N., Indu S., "Comparison of image matching techniques", Volume 7 Issue 3 - September 2016, 396-401
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