The challenging task in image retrieval is to find
similar images based on the distance between images.
Content based image retrieval system is used to identify the
similarity between multidimensional image feature vectors.
If the database is large, searching the image linearly will be
too slow. We have proposed the two dimensional binary tree
approach for searching the images based on feature
detectors and they have improve the retrieval efficiency
significantly.
Published In : IJCSN Journal Volume 5, Issue 1
Date of Publication : February 2016
Pages : 142-145
Figures :01
Tables :
Publication Link : Large Scale Image Searching Using Two Dimensional
Binary Trees Combined with Feature Selection
Radhakrishnan B : is working as Asst.
Professor in Computer Science
department. He has more than 14 years
experience in teaching and has published
papers on data mining and image
processing. His research interests
include image processing, data mining,
and image mining
Anver Muhammed K.M : is working as
System Administrator in Computer
Science department. He has more than
10 years experience in System
Administration and Implementation. His
research interests include image
processing and network security.
Solution of finding the similar image items requires
solving the nearest neighbor problem. Two dimensional
binary search trees are an efficient method for finding nearest neighbors. In this paper we have adapted the
search trees to the problem of image retrieval and found
the best parameters regarding minimizing the access time.
Threshold value can be approximated by a logarithmic
function of the number of feature vectors.
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