Intelligent Image and Video Interpretation: Algorithms and Applications

278 Pages·2013·20.836 MB·English

by  Jing Tian, Jing Tian, Li Chen

Intelligent Image and
Video Interpretation:
Algorithms and Applications
Jing Tian
Wuhan University of Science and Technology, China
Li Chen
Wuhan University of Science and Technology, China
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Editorial Director: Joel Gamon
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Library of Congress Cataloging-in-Publication Data
Intelligent image and video interpretation : algorithms and applications / Jing Tian and Li Chen,
editors.
pages cm
Summary: “This book covers all aspects of image and video analysis from low-level early visions
to high-level recognition, highlighting how these techniques have become applicable and will prove
to be a valuable tool for researchers, professionals, and graduate students working or studying the
fields of imaging and video processing”--Provided by publisher.
Includes bibliographical references and index.
ISBN 978-1-4666-3958-4 (hardcover) -- ISBN 978-1-4666-3959-1 (ebook) -- ISBN 978-1-4666-
3960-7 (print & perpetual access) 1. Image analysis--Research. 2. Image processing--Research. 3.
Artificial intelligence--Research. 4. Digital images--Research. 5. Digital video--Research. I. Tian,
Jing, 1979- II. Chen, Li, 1977-
TA1637.I476 2013
621.36’7--dc23
2012051548
British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book is new, previously-unpublished material. The views expressed in
this book are those of the authors, but not necessarily of the publisher.
Editorial Advisory Board
Lihong Ma, South China University of Technology, China
Da Qi, University of Liverpool, UK
Zhen Qian, Piedmont Heart Institute, USA
Yongtao Wang, Peking University, China
List of Reviewers
Jingyu Hua, Zhejiang University of Technology, China
Zhenyu Liu, Zaozhuang University, China
Chen Wang, Nanyang Technological University, Singapore
Zhe Wei, Nanyang Technological University, Singapore
Xin Xu, Wuhan University of Technology, China
Huanqiang Zeng, Chinese University of Hong Kong, Hong Kong
Table of Contents
Preface....................................................................................................................x
Acknowledgment.................................................................................................xii
Chapter 1
Intelligent.Video.Authentication:.Algorithms.and.Applications.............................1
Saurabh Upadhyay, Banaras Hindu University, India
Shrikant Tiwari, Banaras Hindu University, India
Sanjay Kumar Singh, Banaras Hindu University, India
Chapter 2
Audio.and.Visual.Speech.Recognition.Recent.Trends.........................................42
Lee Hao Wei, Sunway University, Malaysia
Seng Kah Phooi, Sunway University, Malaysia
Ang Li-Minn, Edith Cowan University, Australia
Chapter 3
A.Survey.of.Human.Activity.Interpretation.in.Image.and.Video.Sequence.........87
Xin Xu, Wuhan University of Science and Technology, China
Li Chen, Wuhan University of Science and Technology, China
Xiaolong Zhang, Wuhan University of Science and Technology, China
Dongfang Chen, Wuhan University of Science and Technology, China
Xiaoming Liu, Wuhan University of Science and Technology, China
Xiaowei Fu, Wuhan University of Science and Technology, China
Chapter 4
Review.of.Sparsity.Known.and.Blind.Sparsity.Greedy.Algorithm.for..
Compressed.Sensing...........................................................................................125
Chun-Yan Zeng, South China University of Technology, China
Li-Hong Ma, South China University of Technology, China
Ming-Hui Du, South China University of Technology, China
Jing Tian, Wuhan University of Science and Technology, China
Chapter 5
Adaptive.Edge-Preserving.Smoothing.and.Detail.Enhancement.for.H.263..
and.H.264.Video.................................................................................................139
Ji-Hye Kim, Sogang University, Korea
Ji Won Lee, Sogang University, Korea
Rae-Hong Park, Sogang University, Korea
Min-Ho Park, PIXTREE, Korea
Jae-Seob Shin, PIXTREE, Korea
Chapter 6
Thresholding.Selection.Based.on.Fuzzy.Entropy.and.Bee.Colony..
Algorithm.for.Image.Segmentation....................................................................165
Yonghao Xiao, South China University of Technology, China & Foshan
University, China
Weiyu Yu, South China University of Technology, China & Soochow
University, China
Jing Tian, Wuhan University of Science and Technology, China
Chapter 7
Image.Denoising.via.2-D.FIR.Filtering.Approach.............................................184
Jingyu Hua, Zhejiang University of Technology, China
Wankun Kuang, Zhejiang University of Technology, China
Chapter 8
Optimization.of.Image.Zernike.Moments.Shape.Feature.Based.on..
Evolutionary.Computation..................................................................................199
Maofu Liu, Wuhan University of Science and Technology, China
Huijun Hu, Wuhan University of Science and Technology, China
Chapter 9
Dimension.Reduction.of.Local.Manifold.Learning.Algorithm.for..
Hyperspectral.Image.Classification....................................................................217
Sheng Ding, Wuhan University, China & Wuhan University of Science
and Technology, China
Li Chen, Wuhan University of Science and Technology, China
Jun Li, Wuhan University of Science and Technology, China
Compilation of References...............................................................................232
About the Contributors....................................................................................255
Index...................................................................................................................262
Detailed Table of Contents
Preface....................................................................................................................x
Acknowledgment.................................................................................................xii
Chapter 1
Intelligent.Video.Authentication:.Algorithms.and.Applications.............................1
Saurabh Upadhyay, Banaras Hindu University, India
Shrikant Tiwari, Banaras Hindu University, India
Sanjay Kumar Singh, Banaras Hindu University, India
This.chapter.presents.an.intelligent.video.authentication.algorithm.using.a.support.
vector.machine,.which.is.a.non-linear.classifier.and.its.applications..It.covers.both.
kinds.of.tampering.attacks,.spatial.and.temporal.
Chapter 2
Audio.and.Visual.Speech.Recognition.Recent.Trends.........................................42
Lee Hao Wei, Sunway University, Malaysia
Seng Kah Phooi, Sunway University, Malaysia
Ang Li-Minn, Edith Cowan University, Australia
This.chapter.reviews.audio-visual.speech.recognition.processes.and.relevant.tech-
niques.with.a.specific.focus.on.feature.extraction.and.classification.for.both.audio.
and.visual.processing.
Chapter 3
A.Survey.of.Human.Activity.Interpretation.in.Image.and.Video.Sequence.........87
Xin Xu, Wuhan University of Science and Technology, China
Li Chen, Wuhan University of Science and Technology, China
Xiaolong Zhang, Wuhan University of Science and Technology, China
Dongfang Chen, Wuhan University of Science and Technology, China
Xiaoming Liu, Wuhan University of Science and Technology, China
Xiaowei Fu, Wuhan University of Science and Technology, China
In.image.and.video.sequence.analysis,.human.activity.detection.and.recognition.is.
critically.important..This.chapter.provides.a.comprehensive.review.of.the.recent.
advances.in.human.activity.recognition..Various.methods.for.each.issue.are.discussed.
to.examine.the.state.of.the.art.
Chapter 4
Review.of.Sparsity.Known.and.Blind.Sparsity.Greedy.Algorithm.for..
Compressed.Sensing...........................................................................................125
Chun-Yan Zeng, South China University of Technology, China
Li-Hong Ma, South China University of Technology, China
Ming-Hui Du, South China University of Technology, China
Jing Tian, Wuhan University of Science and Technology, China
This.chapter.reviews.typical.sparsity.known.greedy.algorithms.as.well.as.emerg-
ing.blind.sparsity.greedy.algorithms..Furthermore,.the.algorithms.are.analyzed.
in.structured.diagrammatic.representation.and.compared.by.exact.reconstruction.
probabilities.for.Gaussian.and.binary.sparse.signals.
Chapter 5
Adaptive.Edge-Preserving.Smoothing.and.Detail.Enhancement.for.H.263..
and.H.264.Video.................................................................................................139
Ji-Hye Kim, Sogang University, Korea
Ji Won Lee, Sogang University, Korea
Rae-Hong Park, Sogang University, Korea
Min-Ho Park, PIXTREE, Korea
Jae-Seob Shin, PIXTREE, Korea
This.chapter.proposes.a.pre-processing.method.of.motion-adaptive.edge-preserving.
smoothing.and.detail.enhancement.for.H.263.and.H.264.video.in.which.temporal.
and.spatial.edges.are.used.to.define.a.region.of.interest.
Chapter 6
Thresholding.Selection.Based.on.Fuzzy.Entropy.and.Bee.Colony..
Algorithm.for.Image.Segmentation....................................................................165
Yonghao Xiao, South China University of Technology, China & Foshan
University, China
Weiyu Yu, South China University of Technology, China & Soochow
University, China
Jing Tian, Wuhan University of Science and Technology, China
Image.thresholding.segmentation.based.on.Bee.Colony.Algorithm.(BCA).and.fuzzy.
entropy.is.presented.in.this.chapter..The.fuzzy.entropy.function.is.simplified.within.a.
single.parameter..The.BCA.is.applied.to.search.the.minimum.value.of.fuzzy.entropy.
function.for.obtaining.the.optimal.image.threshold.
Chapter 7
Image.Denoising.via.2-D.FIR.Filtering.Approach.............................................184
Jingyu Hua, Zhejiang University of Technology, China
Wankun Kuang, Zhejiang University of Technology, China
This.chapter.provides.a.comparative.study.of.the.conventional.lowpass.filtering.ap-
proach,.then.proposes.an.improved.method.based.on.learning.method,.where.pixels.
are.filtered.by.five.edge-oriented.filters,.respectively,.facilitated.to.their.edge.details..
Furthermore,.the.differential.evolution.particle.swarm.optimization.algorithm.is.
exploited.to.refine.those.filters.
Chapter 8
Optimization.of.Image.Zernike.Moments.Shape.Feature.Based.on..
Evolutionary.Computation..................................................................................199
Maofu Liu, Wuhan University of Science and Technology, China
Huijun Hu, Wuhan University of Science and Technology, China
The.image.shape.feature.can.be.described.by.the.image.Zernike.moments..This.
chapter.pinpoints.that.the.high.dimension.image.Zernike.moments.shape.feature.
vector.can.describe.more.details.of.the.original.image,.while.it.has.too.many.ele-
ments.making.trouble.for.the.next.image.analysis.phases.
Chapter 9
Dimension.Reduction.of.Local.Manifold.Learning.Algorithm.for..
Hyperspectral.Image.Classification....................................................................217
Sheng Ding, Wuhan University, China & Wuhan University of Science
and Technology, China
Li Chen, Wuhan University of Science and Technology, China
Jun Li, Wuhan University of Science and Technology, China
This.chapter.addresses.the.problems.in.hyperspectral.image.classification.by.the.
methods.of.local.manifold.learning.methods..With.a.proper.selection.of.parameters.
and.a.sufficient.number.of.features,.the.manifold.learning.methods.using.the.k-
nearest.neighborhood.classification.results.produce.an.efficient.and.accurate.data.
representation.that.yields.higher.classification.accuracies.than.conventional.linear.
dimension.reduction.methods.for.the.hyperspectral.image.
Compilation of References...............................................................................232
About the Contributors....................................................................................255
Index...................................................................................................................262