DocumentCode
1776536
Title
Retrieve the similar matching images using reduced SIFT with CED algorithm
Author
Bandaru, Rajanna ; Naik, Dinesh
Author_Institution
Dept. Of Inf. Technol., Nat. Inst. Of Technol. Karnataka, Mangalore, India
fYear
2014
fDate
10-11 July 2014
Firstpage
1242
Lastpage
1247
Abstract
The local feature descriptor called SIFT, is one of the most widely used descriptors. The keypoints found with RSIFT and describe them in a standard way, which makes them invariant to the size changes, rotation, position, scale, and so on. These are quite powerful features and are used in a variety of tasks. This local feature SIFT descriptor gives potential key points, which are extracted from the image. If there are many such key points, a lot of computation time will be required for the matching key points, and some cases one key point matches more than once. For these reasons, here we have tried to reduce the key points in order to cluster the number of key points. The reduced SIFT with Canny Edge Detection (CED) algorithm can easily identify and trace the specified image from large the Database images as much fast as possible.
Keywords
content-based retrieval; edge detection; image matching; image retrieval; transforms; CED algorithm; Canny edge detection algorithm; RSIFT; content based image retrieval; local feature SIFT descriptor; local feature descriptor; similar matching image retrieval; Databases; Feature extraction; Histograms; Image edge detection; Noise; Shape; Transforms; Color Histograms; Content based image retrieval (CBIR); RANSAC; RSIFT with CED; Retrieval; Scale invariant feature transform (SIFT); Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on
Conference_Location
Kanyakumari
Print_ISBN
978-1-4799-4191-9
Type
conf
DOI
10.1109/ICCICCT.2014.6993151
Filename
6993151
Link To Document