Computational intelligence in image processing:
<p>Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consu...
Gespeichert in:
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2013
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| Online-Zugang: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FWS01 UBY01 Volltext Inhaltsverzeichnis Abstract |
| Zusammenfassung: | <p>Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the attention of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research problems and in real-world problems. </p><p>Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can be developed for the purpose of image inferencing. The book offers a unified view of the modern computational intelligence techniques required to solve real-world problems and it is suitable as a reference for engineers, researchers and graduate students.</p> |
| Beschreibung: | <p>Part I - Image Preprocessing Algorithms -- Chap. 1 - Improved Digital Image Enhancement Filters Based on Type-2 Neuro-Fuzzy Techniques (Mehmet Emin Yüksel, Alper Baştürk) -- Chap. 2 - Locally-Equalized Image Contrast Enhancement Using PSO-Tuned Sectorized Equalization (N.M. Kwok, Q.P. Ha, G. Fang, D. Wang, S.Y. Chen) -- Chap. 3 - Hybrid BBO-DE Algorithms for Fuzzy Entropy Based Thresholding (Ilhem Boussaïd, Amitava Chatterjee, Patrick Siarry, Mohamed Ahmed-Nacer) -- Chap. 4 - A Genetic Programming Approach for Image Segmentation (Hugo Alberto Perlin, Heitor Silvério Lopes) -- Part II - Image Compression Algorithms -- Chap. 5 - Fuzzy Clustering-Based Vector Quantization for Image Compression (George E. Tsekouras, Dimitrios M. Tsolakis) -- Chap. 6 - Layers Image Compression and Reconstruction by Fuzzy Transforms (Ferdinando Di Martino, Salvatore Sessa) -- - Chap. 7 - Modified Bacterial Foraging Optimization Technique for Vector Quantization-Based Image Compression (Nandita Sanyal, Amitava Chatterjee, Sugata Munshi) -- Part III - Image Analysis Algorithms -- Chap. 8 - A Fuzzy-Condition-Sensitive Hierarchical Algorithm for Approximate Template Matching in Dynamic Image Sequences (Rajshree Mandal, Anisha Halder, Amit Konar, Atulya K. Nagar) -- Chap. 9 - Digital Watermarking Strings with Images Compressed by Fuzzy Relation Equations (Ferdinando Di Martino, Salvatore Sessa) -- Chap. 10 - Study on Human Brain Registration Process Using Mutual Information and Evolutionary Algorithms (Mahua Bhattacharya, Arpita Das) -- Chap. 11 - On the Use of Stochastic Optimization Algorithms in Image Retrieval Problems (Mattia Broilo, Francesco G.B. De Natale) -- Chap. 12 - A Cluster-Based Boosting Strategy for Red Eyes Removal (Sebastiano Battiato, Giovanni Maria Farinella, Mirko Guarnera, Giuseppe Messina, Daniele Ravì) -- - Part IV - Image Inferencing Algorithms -- Chap. 13 - Classifying Pathological Prostate Images by Fractal Analysis and Texture Features of Multicategories (Po-Whei Huang, Cheng-Hsiung Lee, Phen-Lan Lin) -- Chap. 14 - Multiobjective PSO for Hyperspectral Image Clustering (Farid Melgani, Edoardo Pasolli) -- Chap. 15 - A Computational Intelligence Approach to Emotion Recognition from the Lip-Contour of a Subject (Anisha Halder, Srishti Shaw, Kanika Orea, Pavel Bhowmik, Aruna Chakraborty, Amit Konar) -- Index.</p> |
| Beschreibung: | 1 Online-Ressource (XII, 301 p. 166 illus., 62 illus. in color) |
| ISBN: | 9783642306211 |
| DOI: | 10.1007/978-3-642-30621-1 |
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| 500 | |a <p>Part I - Image Preprocessing Algorithms -- Chap. 1 - Improved Digital Image Enhancement Filters Based on Type-2 Neuro-Fuzzy Techniques (Mehmet Emin Yüksel, Alper Baştürk) -- Chap. 2 - Locally-Equalized Image Contrast Enhancement Using PSO-Tuned Sectorized Equalization (N.M. Kwok, Q.P. Ha, G. Fang, D. Wang, S.Y. Chen) -- Chap. 3 - Hybrid BBO-DE Algorithms for Fuzzy Entropy Based Thresholding (Ilhem Boussaïd, Amitava Chatterjee, Patrick Siarry, Mohamed Ahmed-Nacer) -- Chap. 4 - A Genetic Programming Approach for Image Segmentation (Hugo Alberto Perlin, Heitor Silvério Lopes) -- Part II - Image Compression Algorithms -- Chap. 5 - Fuzzy Clustering-Based Vector Quantization for Image Compression (George E. Tsekouras, Dimitrios M. Tsolakis) -- Chap. 6 - Layers Image Compression and Reconstruction by Fuzzy Transforms (Ferdinando Di Martino, Salvatore Sessa) -- | ||
| 500 | |a - Chap. 7 - Modified Bacterial Foraging Optimization Technique for Vector Quantization-Based Image Compression (Nandita Sanyal, Amitava Chatterjee, Sugata Munshi) -- Part III - Image Analysis Algorithms -- Chap. 8 - A Fuzzy-Condition-Sensitive Hierarchical Algorithm for Approximate Template Matching in Dynamic Image Sequences (Rajshree Mandal, Anisha Halder, Amit Konar, Atulya K. Nagar) -- Chap. 9 - Digital Watermarking Strings with Images Compressed by Fuzzy Relation Equations (Ferdinando Di Martino, Salvatore Sessa) -- Chap. 10 - Study on Human Brain Registration Process Using Mutual Information and Evolutionary Algorithms (Mahua Bhattacharya, Arpita Das) -- Chap. 11 - On the Use of Stochastic Optimization Algorithms in Image Retrieval Problems (Mattia Broilo, Francesco G.B. De Natale) -- Chap. 12 - A Cluster-Based Boosting Strategy for Red Eyes Removal (Sebastiano Battiato, Giovanni Maria Farinella, Mirko Guarnera, Giuseppe Messina, Daniele Ravì) -- | ||
| 500 | |a - Part IV - Image Inferencing Algorithms -- Chap. 13 - Classifying Pathological Prostate Images by Fractal Analysis and Texture Features of Multicategories (Po-Whei Huang, Cheng-Hsiung Lee, Phen-Lan Lin) -- Chap. 14 - Multiobjective PSO for Hyperspectral Image Clustering (Farid Melgani, Edoardo Pasolli) -- Chap. 15 - A Computational Intelligence Approach to Emotion Recognition from the Lip-Contour of a Subject (Anisha Halder, Srishti Shaw, Kanika Orea, Pavel Bhowmik, Aruna Chakraborty, Amit Konar) -- Index.</p> | ||
| 520 | |a <p>Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the attention of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research problems and in real-world problems. </p><p>Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can be developed for the purpose of image inferencing. The book offers a unified view of the modern computational intelligence techniques required to solve real-world problems and it is suitable as a reference for engineers, researchers and graduate students.</p> | ||
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| adam_text | COMPUTATIONAL INTELLIGENCE IN IMAGE PROCESSING
/
: 2013
TABLE OF CONTENTS / INHALTSVERZEICHNIS
PART I - IMAGE PREPROCESSING ALGORITHMS
CHAP. 1 - IMPROVED DIGITAL IMAGE ENHANCEMENT FILTERS BASED ON TYPE-2
NEURO-FUZZY TECHNIQUES (MEHMET EMIN YUEKSEL, ALPER BASTUERK)
CHAP. 2 - LOCALLY-EQUALIZED IMAGE CONTRAST ENHANCEMENT USING PSO-TUNED
SECTORIZED EQUALIZATION (N.M. KWOK, Q.P. HA, G. FANG, D. WANG, S.Y.
CHEN)
CHAP. 3 - HYBRID BBO-DE ALGORITHMS FOR FUZZY ENTROPY BASED THRESHOLDING
(ILHEM BOUSSAID, AMITAVA CHATTERJEE, PATRICK SIARRY, MOHAMED
AHMED-NACER)
CHAP. 4 - A GENETIC PROGRAMMING APPROACH FOR IMAGE SEGMENTATION (HUGO
ALBERTO PERLIN, HEITOR SILVERIO LOPES)
PART II - IMAGE COMPRESSION ALGORITHMS
CHAP. 5 - FUZZY CLUSTERING-BASED VECTOR QUANTIZATION FOR IMAGE
COMPRESSION (GEORGE E. TSEKOURAS, DIMITRIOS M. TSOLAKIS)
CHAP. 6 - LAYERS IMAGE COMPRESSION AND RECONSTRUCTION BY FUZZY
TRANSFORMS (FERDINANDO DI MARTINO, SALVATORE SESSA)
CHAP. 7 - MODIFIED BACTERIAL FORAGING OPTIMIZATION TECHNIQUE FOR VECTOR
QUANTIZATION-BASED IMAGE COMPRESSION (NANDITA SANYAL, AMITAVA
CHATTERJEE, SUGATA MUNSHI)
PART III - IMAGE ANALYSIS ALGORITHMS
CHAP. 8 - A FUZZY-CONDITION-SENSITIVE HIERARCHICAL ALGORITHM FOR
APPROXIMATE TEMPLATE MATCHING IN DYNAMIC IMAGE SEQUENCES (RAJSHREE
MANDAL, ANISHA HALDER, AMIT KONAR, ATULYA K. NAGAR)
CHAP. 9 - DIGITAL WATERMARKING STRINGS WITH IMAGES COMPRESSED BY FUZZY
RELATION EQUATIONS (FERDINANDO DI MARTINO, SALVATORE SESSA)
CHAP. 10 - STUDY ON HUMAN BRAIN REGISTRATION PROCESS USING MUTUAL
INFORMATION AND EVOLUTIONARY ALGORITHMS (MAHUA BHATTACHARYA, ARPITA DAS)
CHAP. 11 - ON THE USE OF STOCHASTIC OPTIMIZATION ALGORITHMS IN IMAGE
RETRIEVAL PROBLEMS (MATTIA BROILO, FRANCESCO G.B. DE NATALE)
CHAP. 12 - A CLUSTER-BASED BOOSTING STRATEGY FOR RED EYES REMOVAL
(SEBASTIANO BATTIATO, GIOVANNI MARIA FARINELLA, MIRKO GUARNERA, GIUSEPPE
MESSINA, DANIELE RAVI)
PART IV - IMAGE INFERENCING ALGORITHMS
CHAP. 13 - CLASSIFYING PATHOLOGICAL PROSTATE IMAGES BY FRACTAL ANALYSIS
AND TEXTURE FEATURES OF MULTICATEGORIES (PO-WHEI HUANG, CHENG-HSIUNG
LEE, PHEN-LAN LIN)
CHAP. 14 - MULTIOBJECTIVE PSO FOR HYPERSPECTRAL IMAGE CLUSTERING (FARID
MELGANI, EDOARDO PASOLLI)
CHAP. 15 - A COMPUTATIONAL INTELLIGENCE APPROACH TO EMOTION RECOGNITION
FROM THE LIP-CONTOUR OF A SUBJECT (ANISHA HALDER, SRISHTI SHAW, KANIKA
OREA, PAVEL BHOWMIK, ARUNA CHAKRABORTY, AMIT KONAR)
INDEX
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
COMPUTATIONAL INTELLIGENCE IN IMAGE PROCESSING
/
: 2013
ABSTRACT / INHALTSTEXT
COMPUTATIONAL INTELLIGENCE BASED TECHNIQUES HAVE FIRMLY ESTABLISHED
THEMSELVES AS VIABLE, ALTERNATE, MATHEMATICAL TOOLS FOR MORE THAN A
DECADE. THEY HAVE BEEN EXTENSIVELY EMPLOYED IN MANY SYSTEMS AND
APPLICATION DOMAINS, AMONG THESE SIGNAL PROCESSING, AUTOMATIC CONTROL,
INDUSTRIAL AND CONSUMER ELECTRONICS, ROBOTICS, FINANCE, MANUFACTURING
SYSTEMS, ELECTRIC POWER SYSTEMS, AND POWER ELECTRONICS. IMAGE PROCESSING
IS ALSO AN EXTREMELY POTENT AREA WHICH HAS ATTRACTED THE ATTENTION OF
MANY RESEARCHERS WHO ARE INTERESTED IN THE DEVELOPMENT OF NEW
COMPUTATIONAL INTELLIGENCE-BASED TECHNIQUES AND THEIR SUITABLE
APPLICATIONS, IN BOTH RESEARCH PROBLEMS AND IN REAL-WORLD PROBLEMS.
PART I OF THE BOOK DISCUSSES SEVERAL IMAGE PREPROCESSING ALGORITHMS;
PART II BROADLY COVERS IMAGE COMPRESSION ALGORITHMS; PART III
DEMONSTRATES HOW COMPUTATIONAL INTELLIGENCE-BASED TECHNIQUES CAN BE
EFFECTIVELY UTILIZED FOR IMAGE ANALYSIS PURPOSES; AND PART IV SHOWS HOW
PATTERN RECOGNITION, CLASSIFICATION AND CLUSTERING-BASED TECHNIQUES CAN
BE DEVELOPED FOR THE PURPOSE OF IMAGE INFERENCING. THE BOOK OFFERS A
UNIFIED VIEW OF THE MODERN COMPUTATIONAL INTELLIGENCE TECHNIQUES
REQUIRED TO SOLVE REAL-WORLD PROBLEMS AND IT IS SUITABLE AS A REFERENCE
FOR ENGINEERS, RESEARCHERS AND GRADUATE STUDENTS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
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| dewey-hundreds | 000 - Computer science, information, general works |
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| discipline | Informatik |
| doi_str_mv | 10.1007/978-3-642-30621-1 |
| format | Electronic eBook |
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Kwok, Q.P. Ha, G. Fang, D. Wang, S.Y. Chen) -- Chap. 3 - Hybrid BBO-DE Algorithms for Fuzzy Entropy Based Thresholding (Ilhem Boussaïd, Amitava Chatterjee, Patrick Siarry, Mohamed Ahmed-Nacer) -- Chap. 4 - A Genetic Programming Approach for Image Segmentation (Hugo Alberto Perlin, Heitor Silvério Lopes) -- Part II - Image Compression Algorithms -- Chap. 5 - Fuzzy Clustering-Based Vector Quantization for Image Compression (George E. Tsekouras, Dimitrios M. 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Nagar) -- Chap. 9 - Digital Watermarking Strings with Images Compressed by Fuzzy Relation Equations (Ferdinando Di Martino, Salvatore Sessa) -- Chap. 10 - Study on Human Brain Registration Process Using Mutual Information and Evolutionary Algorithms (Mahua Bhattacharya, Arpita Das) -- Chap. 11 - On the Use of Stochastic Optimization Algorithms in Image Retrieval Problems (Mattia Broilo, Francesco G.B. 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They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the attention of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research problems and in real-world problems. </p><p>Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can be developed for the purpose of image inferencing. The book offers a unified view of the modern computational intelligence techniques required to solve real-world problems and it is suitable as a reference for engineers, researchers and graduate students.</p></subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Ingenieurwissenschaften</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Künstliche Intelligenz</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Engineering</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer vision</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Datenkompression</subfield><subfield code="0">(DE-588)4121121-2</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield 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| genre | 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV040882160 |
| illustrated | Not Illustrated |
| indexdate | 2024-08-01T16:14:46Z |
| institution | BVB |
| isbn | 9783642306211 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025861884 |
| oclc_num | 812578385 |
| open_access_boolean | |
| owner | DE-898 DE-BY-UBR DE-634 DE-573 DE-92 DE-Aug4 DE-859 DE-706 DE-863 DE-BY-FWS |
| owner_facet | DE-898 DE-BY-UBR DE-634 DE-573 DE-92 DE-Aug4 DE-859 DE-706 DE-863 DE-BY-FWS |
| physical | 1 Online-Ressource (XII, 301 p. 166 illus., 62 illus. in color) |
| psigel | ZDB-2-ENG |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Springer |
| record_format | marc |
| spellingShingle | Computational intelligence in image processing Ingenieurwissenschaften Künstliche Intelligenz Engineering Artificial intelligence Computer vision Datenkompression (DE-588)4121121-2 gnd Vorverarbeitung (DE-588)4403014-9 gnd Bildverarbeitung (DE-588)4006684-8 gnd Soft Computing (DE-588)4455833-8 gnd |
| subject_GND | (DE-588)4121121-2 (DE-588)4403014-9 (DE-588)4006684-8 (DE-588)4455833-8 (DE-588)4143413-4 |
| title | Computational intelligence in image processing |
| title_auth | Computational intelligence in image processing |
| title_exact_search | Computational intelligence in image processing |
| title_full | Computational intelligence in image processing Amitava Chatterjee ..., ed. |
| title_fullStr | Computational intelligence in image processing Amitava Chatterjee ..., ed. |
| title_full_unstemmed | Computational intelligence in image processing Amitava Chatterjee ..., ed. |
| title_short | Computational intelligence in image processing |
| title_sort | computational intelligence in image processing |
| topic | Ingenieurwissenschaften Künstliche Intelligenz Engineering Artificial intelligence Computer vision Datenkompression (DE-588)4121121-2 gnd Vorverarbeitung (DE-588)4403014-9 gnd Bildverarbeitung (DE-588)4006684-8 gnd Soft Computing (DE-588)4455833-8 gnd |
| topic_facet | Ingenieurwissenschaften Künstliche Intelligenz Engineering Artificial intelligence Computer vision Datenkompression Vorverarbeitung Bildverarbeitung Soft Computing Aufsatzsammlung |
| url | https://doi.org/10.1007/978-3-642-30621-1 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025861884&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025861884&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT chatterjeeamitava computationalintelligenceinimageprocessing |