The Resource Image processing & communications challenges 6, Ryszard S. Choraś, editor

Image processing & communications challenges 6, Ryszard S. Choraś, editor

Label
Image processing & communications challenges 6
Title
Image processing & communications challenges 6
Statement of responsibility
Ryszard S. Choraś, editor
Title variation
Image processing and communications challenges 6
Creator
Contributor
Editor
Subject
Genre
Language
eng
Summary
This book collects a series of research papers in the area of Image Processing and Communications which not only introduce a summary of current technology but also give an outlook of potential feature problems in this area. The key objective of the book 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 and presents the proceedings of the 6th International Image Processing and Communications Conference (IP & C 2014) held in Bydgoszcz, 10-12 September
Member of
Cataloging source
GW5XE
Dewey number
006.6
Illustrations
illustrations
Index
index present
LC call number
TA1637
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
2014
http://bibfra.me/vocab/lite/meetingName
International Image Processing and Communications Conference
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Choraś, Ryszard S.
Series statement
Advances in Intelligent Systems and Computing,
Series volume
volume 313
http://library.link/vocab/subjectName
  • Image processing
  • Artificial intelligence
  • Software engineering
  • COMPUTERS
  • Artificial intelligence
  • Image processing
  • Software engineering
Label
Image processing & communications challenges 6, Ryszard S. Choraś, editor
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-10662-5
Instantiates
Publication
Copyright
Note
  • International conference proceedings
  • Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; Table of Contents; Part I Image Processing; Two-Dimensional Hidden Markov Models in Road Signs Recognition; 1 Introduction; 2 Classic 1D HMM; 2.1 Three Basic Problems; 2.2 Solution to Problem 1; 2.3 Solution to Problem 3; 3 2DHMM; 3.1 Solution to 2D Problem 1; 3.2 Solution to 2D Problem 3; 4 Experiments; 5 Conclusion; References; Evaluating the Mutual Position of Objectson the Visual Scene Using MorphologicalProcessing and Reasoning; 1 Introduction; 2 Previous Works; 3 Extracting the Scene Description; 3.1 Finding the Relative Position; 3.2 Distance Computation
  • 3.3 Individual Features3.4 Scene Description Matrix; 4 Reasoning-Based Processing; 4.1 Obtaining the Predicate-Based Description; 4.2 Reasoning about Image Content; 5 Conclusions; References; Vascular Biometry; 1 Introduction; 2 Processing -- Extraction of Vein Structure; 3 Steerable Filters; 4 Radon Transform; 5 Conclusion; References; Clustering-Based Retrieval of Similar Outfits Based on Clothes Visual Characteristics; 1 Introduction; 1.1 Motivation; 1.2 Previous Work; 2 Method Description; 2.1 Feature Extraction; 2.2 Similarity Measure; 2.3 Clustering; 2.4 Similar Outfits Retrieval
  • 3 Experimental Results4 Conclusions; References; Improving Shape Retrieval and ClassificationRates through Low-Dimensional Features Fusion; 1 Introduction; 1.1 Shape as a Descriptor; 1.2 Elementary Shape Descriptors; 1.3 Fusion and Scale Normalization; 2 Experiments; 3 Summary; References; Accelerating the 3D Random Walker ImageSegmentation Algorithm by Image GraphReduction and GPU Computing; 1 Introduction; 2 The Idea of Random Walking for Image Segmentation; 3 Reduction of the Image Graph Size; 4 Image Graph Creation Based on Super-Pixels; 5 Experimental Results; 6 Conclusions; References
  • Computed Tomography Images Denoisingwith Markov Random Field Model Parametrizedby Prewitt Mask1 Introduction; 2 Proposed Algorithm; 2.1 Prewitt Operator; 2.2 Gaussian Filter; 2.3 Markov Random Field Model; 3 Experimental Results; 4 Conclusion; References; Neural Video Compression Algorithm; 1 Introduction; 2 Video Compression Algorithm; 2.1 Neuronal Image Compression; 2.2 Scene Detection; 3 Experimental Result; 4 Conclusions; References; Discovering Important Regions of CytologicalSlides Using Classification Tree; 1 Introduction; 2 Material and Methods; 2.1 Image Database
  • 2.2 Multi-level Thresholding2.3 Discovering Important Regions of Image; 3 Numerical Experiments; 4 Conclusions; References; Gaussian Mixture Model Based Non-Local MeansTechnique for Mixed Noise Suppressionin Color Images; 1 Introduction; 2 Region Homogeneity; 3 Gaussian Mixture Modeling; 4 Non-Local Means Algorithm; 5 Experimental Setup; 6 Noise Suppression Results; 7 Conclusions; References; Robust Image Retrieval Based on MixtureModeling of Weighted Spatio-color Information; 1 Introduction; 2 Gaussian Mixture Modeling; 3 Experimental Setup; 4 Evaluation of the Method Efficiency
Dimensions
unknown
Extent
1 online resource (x, 330 pages)
File format
unknown
Form of item
online
Isbn
9783319106625
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Other control number
10.1007/978-3-319-10662-5
Other physical details
illustrations (some color).
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)890377289
  • (OCoLC)ocn890377289
Label
Image processing & communications challenges 6, Ryszard S. Choraś, editor
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-10662-5
Publication
Copyright
Note
  • International conference proceedings
  • Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; Table of Contents; Part I Image Processing; Two-Dimensional Hidden Markov Models in Road Signs Recognition; 1 Introduction; 2 Classic 1D HMM; 2.1 Three Basic Problems; 2.2 Solution to Problem 1; 2.3 Solution to Problem 3; 3 2DHMM; 3.1 Solution to 2D Problem 1; 3.2 Solution to 2D Problem 3; 4 Experiments; 5 Conclusion; References; Evaluating the Mutual Position of Objectson the Visual Scene Using MorphologicalProcessing and Reasoning; 1 Introduction; 2 Previous Works; 3 Extracting the Scene Description; 3.1 Finding the Relative Position; 3.2 Distance Computation
  • 3.3 Individual Features3.4 Scene Description Matrix; 4 Reasoning-Based Processing; 4.1 Obtaining the Predicate-Based Description; 4.2 Reasoning about Image Content; 5 Conclusions; References; Vascular Biometry; 1 Introduction; 2 Processing -- Extraction of Vein Structure; 3 Steerable Filters; 4 Radon Transform; 5 Conclusion; References; Clustering-Based Retrieval of Similar Outfits Based on Clothes Visual Characteristics; 1 Introduction; 1.1 Motivation; 1.2 Previous Work; 2 Method Description; 2.1 Feature Extraction; 2.2 Similarity Measure; 2.3 Clustering; 2.4 Similar Outfits Retrieval
  • 3 Experimental Results4 Conclusions; References; Improving Shape Retrieval and ClassificationRates through Low-Dimensional Features Fusion; 1 Introduction; 1.1 Shape as a Descriptor; 1.2 Elementary Shape Descriptors; 1.3 Fusion and Scale Normalization; 2 Experiments; 3 Summary; References; Accelerating the 3D Random Walker ImageSegmentation Algorithm by Image GraphReduction and GPU Computing; 1 Introduction; 2 The Idea of Random Walking for Image Segmentation; 3 Reduction of the Image Graph Size; 4 Image Graph Creation Based on Super-Pixels; 5 Experimental Results; 6 Conclusions; References
  • Computed Tomography Images Denoisingwith Markov Random Field Model Parametrizedby Prewitt Mask1 Introduction; 2 Proposed Algorithm; 2.1 Prewitt Operator; 2.2 Gaussian Filter; 2.3 Markov Random Field Model; 3 Experimental Results; 4 Conclusion; References; Neural Video Compression Algorithm; 1 Introduction; 2 Video Compression Algorithm; 2.1 Neuronal Image Compression; 2.2 Scene Detection; 3 Experimental Result; 4 Conclusions; References; Discovering Important Regions of CytologicalSlides Using Classification Tree; 1 Introduction; 2 Material and Methods; 2.1 Image Database
  • 2.2 Multi-level Thresholding2.3 Discovering Important Regions of Image; 3 Numerical Experiments; 4 Conclusions; References; Gaussian Mixture Model Based Non-Local MeansTechnique for Mixed Noise Suppressionin Color Images; 1 Introduction; 2 Region Homogeneity; 3 Gaussian Mixture Modeling; 4 Non-Local Means Algorithm; 5 Experimental Setup; 6 Noise Suppression Results; 7 Conclusions; References; Robust Image Retrieval Based on MixtureModeling of Weighted Spatio-color Information; 1 Introduction; 2 Gaussian Mixture Modeling; 3 Experimental Setup; 4 Evaluation of the Method Efficiency
Dimensions
unknown
Extent
1 online resource (x, 330 pages)
File format
unknown
Form of item
online
Isbn
9783319106625
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Other control number
10.1007/978-3-319-10662-5
Other physical details
illustrations (some color).
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)890377289
  • (OCoLC)ocn890377289

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