Keyblock for Content-based Image Retrieval (Vector quantization Comparison In Piercing Domain Image)
ABSTRACT: Keyblock is a generalization of
the text-based information
retrieval technology in
the image domain. The main
purpose of this framework is to find the codebook of a given size from a set of
training image blocks. This main purpose can be achieved with any Vector
quantization algorithm. This paper is an answer to the questions: “Can we use
keyblock for piercing pattern?” Which one is the best algorithm between GLA or
PNNA for VQ ?” The paper begins by describing some basic theory of Texture
Feature, Keyblock-based, Vector quantization,
Generalized Lloyd Algorithm
(GLA) and Pairwise
Nearest Neighbour Algorithm
(PNNA). Next, it summarizes the implementation of both algorithm in keyblock framework
for piercing pattern. Finally, it describes the experimental result of this
research.
Keywords: Feature Selection,
Pairwise Nearest Neighbor
Algorithm, Texture Analysis,
Keyblock extraction
Author: I Gusti Agung Gede
Arya Kadyanan, Wahyudi, dan Aniati Murni Arymurthy
Journal Code: jptkomputergg120002
