Abstract
In the field of image processing, a piece of information can be defined as a feature, which can be utilised to determine the computational task with references to some applications. Features may refer to specific structures in the images such as points, edges or objects. Feature detection and feature description are the initial steps of image registration process. There are many algorithms of feature detection like BRISK, FAST, SURF, etc. In our earlier paper [15], a hybrid algorithm for feature detection and feature description has been proposed. The next step of image registration is feature matching. This paper deals with feature matching algorithm using BRISK [4], FAST [3] and hybrid [15]. The proposed hybrid algorithm performs better results than the above two existing algorithms in terms of elapsed time, CPU time and performance measuring time. This can be clearly concluded that the feature matching result of hybrid in terms of tables and figures performs well. For testing the algorithm, river dam images of Odisha are chosen.
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