Color Image Retrieval System Based on Shape and
Texture Watermarks
Hao Zhang, Hua Chen*, Fa-Xin Yu and Zhe-Ming Lu
School of Aeronautics and Astronautics
Zhejiang University
Hangzhou 310027, China
Email: chen2013571@126.co m; zheminglu@zju.edu.cn
Abstract—Content-based image retrieval (CBIR) is one of the
most exciting and fastest-growing areas in the field of multimedia
technology. In this Letter, we apply the watermarking technique
into the retrieval system and propose a novel approach for JEPG
image retrieval. The proposed image retrieval system consists of
two main phases, offline process and online retrieval process. The
feature vector is extracted from each image as the watermark to
be embedded into the image, which is the preprocessing
operation called offline process. It doesn’t require decompressing
the JPEG images but directly embedding the watermark in the
DCT domain. The online retrieval process consists of three
processes, i.e., query feature computation, watermark extraction
and feature vector matching. Since the features are embedded in
the image data, it is unnecessary to compute the features but only
to extract it from the watermarked image. We carry out a series
of experiments on a watermarked image database, and the
detailed comparison results between the novel approach and the
traditional system indicate the advantage of the proposed method.
Keywords-image retrieval; content-based image retrieval;
digital image watermarking
I. INTRODUCT ION
With the explosive growth of the image databases in terms
of both the size and the variety, more and more attention has
been paid to the research of automatic image retrieval. Content-
based image retrieval (CBIR), which was proposed in the early
1990’s[1], has been one of the most active research areas in the
past two decades. Many image features, such as color, texture
and shape have been explored to describe the content of the
images and many CBIR systems have been established. Most
existing CBIR systems focus primarily on feature analysis,
similarity measures and feedback learning algorithms [2], as
shown in Fig.1. However, there is no significant effort to
investigate the security problem in CBIR, except Forsyth et
al.’s filter for detecting naked people [3]. Actually, with the
rapid development of digital metadata over the Internet, the
security problem is becoming more and more obvious. For
example, for a remote sensing image database or a face
database, the database has to be open to all the uses without
any authorization [4].
Digital watermarking technology, as an approach of
embedding some information into the image for solving the
security problem, was formed in the middle 1990’s. Digital
watermark is the infor mation ins erted into the host digital
multimedia such as image, video, audio and text. The process
to insert a digital watermark is called digital watermarking.
Digital watermarking is an important approach to ensure the
security of information. It may be widely used in copyright
protection, labeling, monitoring, tamper proofing, conditional
access, national defense, national security, and so on. It has
been a hotspot in the information security field.
Figure 1. T he traditional retrieval system.
Therefore, considering the security problem in the evolving
CBIR systems, watermarking techniques used in CBIR have
been investigated in recent years [4, 5]. In this Letter, we
combine the two relatively new research fields together and
present a novel retrieval system based on the watermarking
technique. The feature vectors are computed as watermarks and
invisibly embedded into images, by which the watermarked
image database is formed during the offline processing phase.
Traditionally, during the offline process, the image retrieval
system for JPEG images needs firstly decompressing the
images and then performing the feature extraction in the spatial
The project is supported by the National Natural Science Foundation of
China under grant No. 61171150 .
Vectors
Retrieval
Results
Formation
2012 Second International Conference on Instrumentation & Measurement, Computer, Communication and Control
978-0-7695-4935-4/12 $26.00 © 2012 IEEE
DOI 10.1109/IMCCC.2012.141
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