Features Deletion on Multiple Objects Recognition
Abstract: This paper presents
a multiple objects recognition method using the SURF and the SIFT algorithm.
Both algorithms are used for finding features by detecting keypoints and
extracting descriptors on every object. The randomized KD-Tree algorithm is
then used for matching those descriptors. The proposed method is deletion of
certain features after an object has been registered and repetition ofsuccessful
recognition. The method is expected to recognize all of the registered objects
which are shown in an image. A series of tests is done in order to understand
the characteristic of the recognizable object and the method capability to do
the recognition. The test results show the accuracy of the proposed method is
97% using SURF and 88.7% using SIFT.
Author: Samuel Alvin Hutama, Saptadi
Nugroho, Darmawan Utomo
Journal Code: jptkomputergg160290