THE NEW NOTION DISTANCE OF CONTENT BASED IMAGE RETRIEVAL (CBIR)
Abstract: This paper proposes
a new notion distance on the CBIR process which is derived from the measure of
multivariate dispersion called vector variance (VV). The minimum vector
variance (MVV) estimator is robust estimator having the high breakdown point.
The CBIR is a retrieval technique using the visual information by retrieving
collections of digital images. The process of retrieval is carried out by
measuring the similarity between query image and the image in the database through
similarity measure. Distance is a metric often used as similarity measure on
CBIR. The query image is relevant to an image in the database if the value of similarity
measure is ’small’. This means that a good CBIR retrieval system mustbe
supported by an accurate similarity measure. The classical distance is
generated from the arithmetic mean which is vulnerable to the masking effect.
The appearance of extreme data causes the inflation of deviation of the
arithmetic mean, this impliesthe distance between the extreme data or the
outlier becomes closer than it supposedto be. In the end of section we discuss
the high performance of the MVV robust distance to CBIR process.
Key words and Phrases: High Breakdown Point, Image Retrieval, Query
image, Similarity Measure, Image Visual Content
Author: Dyah E. Herwindiati,
Sani M. Isa, and Rahmat Sagara
Journal Code: jpmatematikagg100008
