Image Retrieval and Analysis Using Text and Fuzzy Shape Features: Emerging Research and Opportunities

193 Pages·2018·10.938 MB·English

by  P. Sumathy, P. Shanmugavadivu, A. Vadivel

Image Retrieval and
Analysis Using Text and
Fuzzy Shape Features:
Emerging Research and
Opportunities
P. Sumathy
Bharathidasan University, India
P. Shanmugavadivu
Gandhigram Rural Institute, India
A. Vadivel
National Institute of Technology Tiruchirappalli, India
A volume in the Advances in
Multimedia and Interactive
Technologies (AMIT) Book Series
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Library of Congress Cataloging-in-Publication Data
Names: Sumathy, P., 1975- author. | Shanmugavadivu, P., 1967- author. |
Vadivel, A., 1979- author.
Title: Image retrieval and analysis using text and fuzzy shape features :
emerging research and opportunities / by P. Sumathy, P. Shanmugavadivu,
and A. Vadivel.
Description: Hershey, PA : Information Science Reference, [2018] | Includes
bibliographical references.
Identifiers: LCCN 2017022537| ISBN 9781522537960 (hardcover) | ISBN
9781522537977 (ebook)
Subjects: LCSH: Image analysis. | Fuzzy systems. | Content-based image
retrieval.
Classification: LCC TA1637 .S786 2018 | DDC 006.4/2--dc23 LC record available at https://lccn.
loc.gov/2017022537

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Titles in this Series
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Handbook of Research on Advanced Concepts in Real-Time Image and Video Processing
Md. Imtiyaz Anwar (National Institute of Technology, Jalandhar, India) Arun Khosla
(National Institute of Technology, Jalandhar, India) and Rajiv Kapoor (Delhi Technological
University, India)
Information Science Reference • ©2018 • 504pp • H/C (ISBN: 9781522528487) • US $265.00
Transforming Gaming and Computer Simulation Technologies across Industries
Brock Dubbels (McMaster University, Canada)
Information Science Reference • ©2017 • 297pp • H/C (ISBN: 9781522518174) • US $210.00
Feature Detectors and Motion Detection in Video Processing
Nilanjan Dey (Techno India College of Technology, Kolkata, India) Amira Ashour (Tanta
University, Egypt) and Prasenjit Kr. Patra (Bengal College of Engineering and Technology, India)
Information Science Reference • ©2017 • 328pp • H/C (ISBN: 9781522510253) • US $200.00
Mobile Application Development, Usability, and Security
Sougata Mukherjea (IBM, India)
Information Science Reference • ©2017 • 320pp • H/C (ISBN: 9781522509455) • US $180.00
Applied Video Processing in Surveillance and Monitoring Systems
Nilanjan Dey (Techno India College of Technology, Kolkata, India) Amira Ashour (Tanta
University, Egypt) and Suvojit Acharjee (National Institute of Technology Agartala, India)
Information Science Reference • ©2017 • 321pp • H/C (ISBN: 9781522510222) • US $215.00
Intelligent Analysis of Multimedia Information
Siddhartha Bhattacharyya (RCC Institute of Information Technology, India) Hrishikesh
Bhaumik (RCC Institute of Information Technology, India) Sourav De (The University of
Burdwan, India) and Goran Klepac (University College for Applied Computer Engineering
Algebra, Croatia & Raiffeisenbank Austria, Croatia)
Information Science Reference • ©2017 • 520pp • H/C (ISBN: 9781522504986) • US $220.00
For an enitre list of titles in this series, please visit:
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Table of Contents
Preface...................................................................................................................vi
Chapter 1
Text-Based.Image.Retrieval....................................................................................1
Chapter 2
Content-Based.Image.Retrieval.Using.Shape.Features........................................39
Chapter 3
Fuzzy.Object.Shape.for.Image.Retrieval..............................................................62
Chapter 4
Encoding.and.Indexing.Fuzzy.Object.Shape.for.Image.Retrieval........................87
Chapter 5
Similarity.Measure.for.Matching.Fuzzy.Object.Shapes.....................................118
Chapter 6
Textual-Shape-Based.Image.Retrieval................................................................137
Related Readings...............................................................................................158
About the Authors.............................................................................................180
Index...................................................................................................................182
vi
Preface
INTRODUCTION
The ever-growing potential of internet is exponentially increasing the scope
and applications of Multimedia Information Retrieval Systems which in turn
has triggered the development of novel and robust techniques for extracting
contextually relevant text and/or images. The issues and challenges associated
with the information retrieval systems for World Wide Web (WWW) has led
to the emergence of a new dimension in the domain of Text Based Image
Retrieval (TBIR) and Content Based Image Retrieval (CBIR) Systems. The
effectiveness of any information retrieval systems is governed by two primary
features namely, contextual precision of the information to be extracted and
the time duration of retrieval. As the population of images used by various
applications is growing explosively, there is compelling demand on the
researchers to evolve newer techniques for image retrieval, which would
outperform the existing ones. This book presents new ideas and techniques
on image retrieval.
ABOUT THE BOOK
This book brings together an identifiable ‘core’ of Image Retrieval (IR) ideas,
techniques, and applications using text based and content based approaches. It is
indented for researchers working in the field of Content-Based Image Retrieval
and Text-Based Image Retrieval are the target audience. It is the outgrowth
of graduate course taught in the Department of Computer Engineering and
Information Technology. We realized the need to the research scholars who
are working in the field of Image Retrieval using the content of image and
textual information and as a result it is a combined product made up of Text
Based Image Retrieval and Content Based Image Retrieval.
Preface
The novel text based and content-based concept of image handling needs
to be integrated with more traditional semantics. Image Retrieval focuses
on the tools of processing and searching applicable to the content-based
management of new multimedia documents.
ORGANIZATION OF THE BOOK
This book contains six chapters and the details of the book are presented as
follows.
Chapter 1 discusses introduction to TBIR and CBIR with suitable example
and application domains. It also presents related theories and puts forward
new methodologies along with the results and analysis. It explains newly
developed method for ranking the images in Web documents based on the
properties of HTML TAGS in web documents for image retrieval from WWW.
Chapter 2 presents CBIR methodologies for extracting geometric and margin
features of objects in images. Various properties of objects are calculated and
constructed as feature vector. This approach is unique in nature as the size of
the feature is relatively small and capable of discriminating the query object
with the datbase object. The performance of the feature is tested in CBIR
application using precision and recall metrics.
This method is extended in Chapter 3 by estimating the fuzziness associated
with the geometric and margin properties of objects in images. The Fuzzy-
Object-Shape (FOS) feature of images are extracted for each object. The
closeness of each object with primitive shapes is estimated using fuzzy
membership function and constructed as feature vector. The FOS technique
is divised out of this research study that explores fuzzy shapes to capture the
shape of an object of interest along with the degree of impreciseness in the
boundary information which provides a measure of closeness of the object of
interest with reference to the well-known shapes and the similarity measure.
Indexing is very important for image retrieval applications. It is imperative
that a suitable indexing mechanism is required for effectively indexing low-
level feature. The indexed feature can be combined with textual feature for
facilitating shape based retrieval in Chapter 4. In addition, a Fuzzy-Object-
Level image matching algorithm is proposed for measuring the similarity
between the query and database images.
The working principle of proposed similarity measure is explained in
Chapter 5 for measuring the degree of closeness of objects present in both
vii
Preface
query and database images. A Common Bin Similarity Measure (CBSM) is
proposed for ranking the images using the encoded feature.
A suitable indexing mechanism that combines the text features with shape
features (encoded and normal) for text-shape based retrieval is proposed
in Chapter 6. This technique combines the text information with the shape
information to enhance the retrieval performance. In addition, this method
encode the shape features reduce the size of the feature database with good
precision of retrieval.
All the chapter highlights the research insights with relevant experimental
results, analysis and illustration.
To sum up the book, new strategies are being devised based on Strength
Matrix (SM), Tag Ranking Image Retrieval (TRIR), Geometric Margin
based Shape Features of Object (GMSFO), Fuzzy Object Shape for Image
Retrieval (FOSIR) and Indexing Shape Pattern combining text features
with shape features for Shape Based Image Retrieval. These newly devised
techniques to be a valuable addition to the domain of Multimedia Information
Retrieval Systems, due to their assured performance and greater importance
that qualify themselves.
KEY FEATURES OF THE BOOK
The following are the important features of the book:
• Gives a complete picture of TBIR and CBIR approches for Multimedia
Information Retrieval (MIR)
• Proposes a novel conceptualisation around the ideas of Image Retrieval
(IR)
• Use the text around the images in web documents for image retrival
applications
• Understands the syntatical context and textual context of images in
web document
• Defines margin based propertices of objects in images to capture the
shape information
• Formulates FOS properties for capturing impreciseness of shape
information
• Proposes a novel similarity measure for matching FOS objects
viii
Preface
• Designs a newer pattren based indexing scheme to index large number
of low level features
• Combines content based and text based pattern for imporving semantic
understanding for effective CBIR applications
• Relevant for both library and information science and information
technology specialists
ix