Image Processing and Communications Challenges 5

421 Pages·2014·26.01 MB·English

by  Dorota Oszutowska-Mazurek, Przemysław Mazurek, Kinga Sycz, Grażyna Waker-Wójciuk (auth.), Ryszard S. Choras (eds.)

Advances in Intelligent Systems and Computing 233
Ryszard S. Choraś
Editor
Image Processing
and Communications
Challenges 5
Advances in Intelligent Systems and Computing
Volume 233
SeriesEditor
JanuszKacprzyk,Warsaw,Poland
Forfurthervolumes:
http://www.springer.com/series/11156
Ryszard S. Choras´
Editor
Image Processing
and Communications
Challenges 5
ABC
Editor
RyszardS.Choras´
InstituteofTelecommunications
UniversityofTechnologyLifeSciences
Bydgoszcz
Poland
ISSN2194-5357 ISSN2194-5365 (electronic)
ISBN978-3-319-01621-4 ISBN978-3-319-01622-1 (eBook)
DOI10.1007/978-3-319-01622-1
SpringerChamHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2013944663
(cid:2)c SpringerInternationalPublishingSwitzerland2014
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Preface
Itgivesusgreatpleasuretopresentthebook/proceedingsofthe5thInterna-
tional Conference in Image Processing & Communications IP&C 2013, held
inBydgoszcz,Poland,inSeptember2013.The2013InternationalConference
on Image Processing and Communications (IP&C 2013) placed emphasis on
efficientandeffectiveimageprocessingandcommunicationstechnologiesand
systems.
The key objective of the book/proceedings is to provide a collection of
comprehensive references on some recent theoretical development as well as
novel applications in image processing and communications.
The book is divided into two parts. Part I deals with image processing.
A comprehensive survey of different methods of image processing, computer
vision is also presented. Part II deals with the telecommunications networks
and computer networks.Applications in these areas are considered.
Inconclusion,theeditedbookcomprisespapersondiverseaspectsofimage
processingandcommunicationssystems.Therearetheoreticalaspectsaswell
as application papers.
Contents
Part I: Image Processing
Adaptive Windowed Threshold for Box Counting
Algorithm in Cytoscreening Applications
Dorota Oszutowska-Mazurek, Przemysław Mazurek, Kinga Sycz,
Grażyna Waker-Wójciuk ........................................ 3
1 Introduction ............................................... 3
2 Threshold Based Box–Counting .............................. 5
3 Adaptive Windowed Thresholding ............................ 7
4 Example Results ........................................... 9
5 Discussion and Conclusions.................................. 10
References .................................................... 11
Corneal Endothelial Grid Structure Factor Based on
Coefficient of Variation of the Cell Sides Lengths
Jolanta Gronkowska-Serafin, Adam Piórkowski..................... 13
1 Introduction ............................................... 13
2 Shape Factors Used for Describing Corneal Endothelial.......... 14
2.1 Average Coefficient of Variation of the Cell Sides Lengths ... 14
3 The Method of Determining Cells Sides Lengths................ 15
4 Assessment of CVSL Factor Application for Synthetic Models.... 16
5 Conclusion ................................................ 18
References .................................................... 19
A Distributed Approach for Development of Deformable
Model-Based Segmentation Methods
Daniel Reska, Cezary Boldak, Marek Kretowski .................... 21
1 Introduction ............................................... 21
2 Background and Related Work............................... 22
3 Web-Based Segmentation Framework ......................... 23
4 Distributed Solution ........................................ 24
4.1 Task Distribution...................................... 24
VIII Contents
4.2 Single Task Parallelization .............................. 25
5 Experimental Evaluation .................................... 25
6 Conclusion ................................................ 27
References .................................................... 28
Enhancement of Low-Dose CT Brain Scans Using
Graph-Based Anisotropic Interpolation
Tomasz Węgliński, Anna Fabijańska .............................. 29
1 Introduction ............................................... 29
2 Problem Definition ......................................... 30
3 Graph-Based Image Intensity Interpolation .................... 31
4 The Proposed Approach..................................... 32
5 Results and Discussion...................................... 33
6 Conclusions................................................ 36
References .................................................... 36
Using of EM Algorithm to Image Reconstruction Problem
with Tomography Noises
Piotr Dobosz, Robert Cierniak ................................... 37
1 Introduction ............................................... 37
2 Image Reconstruction Algorithm ............................. 38
2.1 The Back-ProjectionOperation.......................... 39
2.2 The Reconstruction Process Using EM-Type Algorithm..... 39
3 Experimental Results ....................................... 40
4 Conclusions................................................ 42
References .................................................... 42
Preprocessing Using Maximal Autocovariance for
Spatio–Temporal Track–Before–Detect Algorithm
Przemysław Mazurek ........................................... 45
1 Introduction ............................................... 45
2 Spatio–Temporal Track–Before–DetectAlgorithm .............. 47
3 Preprocessing of Measurement Space Using Maximal
Autocovariance ............................................ 48
4 Example Results ........................................... 49
4.1 Example: Random Signal – Different Distributions ......... 49
4.2 Example: Periodic Pattern Inside Gaussian Noise .......... 50
4.3 Example: Filtered Random Signal........................ 51
5 Discussion and Conclusions.................................. 52
References .................................................... 52
Which Color Space Should Be Chosen for Robust Color
Image Retrieval Based on Mixture Modeling
Maria Łuszczkiewicz-Piątek ..................................... 55
1 Introduction ............................................... 55
2 Analyzed Color Spaces...................................... 56
Contents IX
3 Image Retrieval Scheme ..................................... 57
4 Experimental Results ....................................... 59
5 Conclusions................................................ 62
References .................................................... 63
The Perception of Humanoid Robot by Human
Rafał Stęgierski, Karol Kuczyński ................................ 65
1 Introduction ............................................... 65
2 Background ............................................... 65
3 Assumption ............................................... 66
4 Humanoid Platform ........................................ 66
5 Software Controller......................................... 66
6 Experiments ............................................... 67
7 Results.................................................... 68
8 Conclusions................................................ 71
References .................................................... 71
A Fast Histogram Estimation Based on the Monte Carlo
Method for Image Binarization
Piotr Lech, Krzysztof Okarma, Mateusz Tecław .................... 73
1 Introduction ............................................... 73
2 Proposed Method .......................................... 74
3 Discussion of Experimental Results ........................... 76
3.1 Results of Fast Histogram Estimation .................... 76
3.2 Comparison of Binarization Results ...................... 76
4 Conclusions and Future Work................................ 78
References .................................................... 80
Adaptation of the Combined Image Similarity Index for
Video Sequences
Krzysztof Okarma.............................................. 81
1 Introduction ............................................... 81
2 Recently Proposed Image Quality Metrics Well Correlated with
Subjective Assessment ...................................... 82
3 Motivation ................................................ 83
4 Image and Video Quality Assessment Datasets ................. 84
5 The Idea of Combined Quality Metrics and the Proposed
Metric .................................................... 85
6 Conclusions................................................ 87
References .................................................... 88
Time-Frequency Analysis of Image Based on Stockwell
Transform
Ryszard S. Choraś ............................................. 91
1 Introduction ............................................... 91
2 ST-Transform ............................................. 92
X Contents
2.1 Continuous ST-Transform .............................. 92
2.2 The Discrete ST-Transform............................. 93
2.3 Two-Dimensional ST-Transform ......................... 93
2.4 2D Discrete Orthonormal ST-Transform (DOST).......... 94
3 Feature Extraction ......................................... 95
4 Conclusion ................................................ 96
References .................................................... 97
Real-Time Recognition of Selected Karate Techniques
Using GDL Approach
Tomasz Hachaj, Marek R. Ogiela, Marcin Piekarczyk ............... 99
1 Introduction ............................................... 99
2 Materials and Methods...................................... 100
2.1 GDL and GDL Script .................................. 100
2.2 Hardware Set-Up and Calibration........................ 100
2.3 Data Set and Classifier Fitting .......................... 103
3 Results.................................................... 104
4 Discussion................................................. 105
5 Conclusion ................................................ 105
References .................................................... 105
2DKLT-Based Color Image Watermarking
Paweł Forczmański............................................. 107
1 Introduction ............................................... 107
2 Algorithm Description ...................................... 109
2.1 Processing Scheme ..................................... 109
2.2 2DKLT Principles ..................................... 109
2.3 Watermark Embedding/Recovering ...................... 110
2.4 Watermarking Quality/Robustness Evaluation............. 111
3 Experiments ............................................... 112
4 Summary.................................................. 113
References .................................................... 114
KnowledgeTransformations AppliedinImage Classification
Task
Krzysztof Wójcik............................................... 115
1 Paper Objectives and Bibliography Remarks .................. 115
2 Knowledge Representation and Learning Scheme ............... 116
3 Examples of Knowledge Structure Joining .................... 117
3.1 Partial Knowledge Building ............................ 117
3.2 Image Classification Task ............................... 119
3.3 Main Features of OTO Method in Comparison with Other
Approaches ........................................... 121
4 Conclusions................................................ 122
References .................................................... 122
Contents XI
Problems of Infrared and Visible-Light Images Automatic
Registration
Karol Kuczyński, Rafał Ste¸gierski ................................ 125
1 Introduction ............................................... 125
2 Materials and Methods...................................... 126
3 Results.................................................... 128
4 Discussion................................................. 128
5 Conclusion ................................................ 131
References .................................................... 132
Computational Complexity Analysis of Adaptive
Arithmetic Coding in HEVC Video Compression Standard
Damian Karwowski ............................................ 133
1 Introduction ............................................... 133
2 HEVC Video Compression – CABAC Entropy Coding .......... 134
3 Complexity Analysis of CABAC in HEVC – Methodology ....... 136
4 Complexity of CABAC in HEVC – Results .................... 137
5 Conclusions................................................ 141
References .................................................... 142
Object Detection and Segmentation Using Adaptive
MeanShift Blob Tracking Algorithm and Graph Cuts
Theory
Boudhane Mohcine, Nsiri Benayad ............................... 143
1 Introduction ............................................... 143
2 Architecture ............................................... 144
3 Theories Concept........................................... 146
4 Algorithm and Theory ..................................... 148
5 Experimental Result ....................................... 149
6 Conclusion ................................................ 150
References .................................................... 151
Semantics Driven Table Understanding in Born-Digital
Documents
Jacek Siciarek ................................................. 153
1 Introduction ............................................... 153
2 Table Structure ............................................ 155
2.1 Table Model .......................................... 155
3 Logical Structure of PDF Document Content .................. 155
3.1 Content Structure Distortion............................ 156
3.2 Content Structure Degradation .......................... 156
4 Table Semantics............................................ 157
4.1 Reverse MVC method .................................. 158
5 Conclusions................................................ 159
References .................................................... 160