Local Tetra Pattern for Image Retrieval System Using Hadoop

Authors

  • Mrs. Urvashi Trivedi Student of Mast er of engineering Department of C o m put er Engineering, Sigma Institute of Technology, V ad o da r
  • Mrs. Kishori Shekoker Assistant Professor,Department of Computer Engineering, Sigma Institute of Technology, V a do d ar a

Keywords:

Map-Reduce, HDFS, Content-Based Image Retrieval (CBIR), Local Tetra Patterns (LTrPs), Hadoop.

Abstract

In today's world, huge quantity of data, in the form
of images, is produced through digital cameras, mobile phones
and photo editing software. It is important to develop new
CBIR techniques which gives effective and scalable result for
real time processing of large image collections. Local tetra
pattern (LTrP) is used for managing the large database. The
local ternary pattern and local binary pattern encode the
relationship. LBP and LTP encodes the relationship between
referenced pixel and its surrounding neighbors by calculating
gray-level difference. Local Tetra Pattern (LTrP) which
carries the interrelationship in between the center pixels and
its surrounded neighbors of center pixel. The main objective
of study is distribution of image data over a large number of
nodes over Hadoop using Map Reduce Technique. Hadoop
defines a framework which allows processing on distributed
large sets across clusters of computer.

Published

2022-04-27

How to Cite

Mrs. Urvashi Trivedi, & Mrs. Kishori Shekoker. (2022). Local Tetra Pattern for Image Retrieval System Using Hadoop. International Journal of Advance Engineering and Research Development (IJAERD), 2(13), -. Retrieved from http://ijaerd.com/index.php/IJAERD/article/view/5683