TITLE:
A New Content Based Image Retrieval Model Based on Wavelet Transform
AUTHORS:
Davar Giveki, Ali Soltanshahi, Fatemeh Shiri, Hadis Tarrah
KEYWORDS:
CBIR, Wavelet Transform, Color Moments, Image Division, RGB Color Space, HSV Color Space, YUV Color Space, YCbCr Color Space, Lab Color Space
JOURNAL NAME:
Journal of Computer and Communications,
Vol.3 No.3,
March
17,
2015
ABSTRACT:
Searching interested images based on visual
properties of images is a challenging problem and it has received considerable
attention from researchers in the fields like image processing, computer vision
and multimedia systems in the last 20 years. While the importance and the
effect of the image features like color, texture and shape have been taken into
account in many papers, there have not been many studies on the importance of
the color spaces on the performance of Content Based Image Retrieval (CBIR)
systems. In this paper we first experimentally study the effect of choosing
color space on the performance of content based image retrieval using Wavelet
decomposition of each color channel. To this end, the retrieval results of
different color spaces like RGB, YUV, HSV, YCbCr and Lab are analyzed. Then as
a result a new Content Based Retrieval model using Wavelet Transform in Lab
color space and Color Moments is proposed. In order to increase the efficiency
of the proposed model some division schemes are taken into account which
improves the performance of the proposed model. The proposed model tackles one
of the important restrictions in content based image retrieval, namely, the
challenge between the accuracy of retrieval and its time complexity. The
experimental results on two databases [19] [24] demonstrate the superiority of
the proposed model compared to existing models.