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Genetic learning for adaptive image segmentation

Genetic learning for adaptive image segmentation

자료유형
단행본
개인저자
Bhanu, Bir. Lee, Sungkee, 1956-.
서명 / 저자사항
Genetic learning for adaptive image segmentation / Bir Bhanu, Sungkee Lee.
발행사항
Boston :   Kluwer Academic Publishers,   c1994.  
형태사항
xix, 271 p. : ill. ; 24 cm.
총서사항
The Kluwer international series in engineering and computer science ;287. Robotics.
ISBN
0792394917 (acid-free paper)
서지주기
Includes bibliographical references (p. [261]-267) and index.
일반주제명
Image processing. Machine learning. Computer vision.
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008 940623s1994 maua b 001 0 eng
010 ▼a 94022448
020 ▼a 0792394917 (acid-free paper)
040 ▼a DLC ▼c DLC
049 1 ▼l 121018982 ▼f 과학
050 0 0 ▼a TA1634 ▼b .B47 1994
082 0 0 ▼a 006.3/7 ▼2 20
090 ▼a 006.37 ▼b B575g
100 1 0 ▼a Bhanu, Bir.
245 1 0 ▼a Genetic learning for adaptive image segmentation / ▼c Bir Bhanu, Sungkee Lee.
260 0 ▼a Boston : ▼b Kluwer Academic Publishers, ▼c c1994.
300 ▼a xix, 271 p. : ▼b ill. ; ▼c 24 cm.
440 4 ▼a The Kluwer international series in engineering and computer science ; ▼v 287. ▼p Robotics.
504 ▼a Includes bibliographical references (p. [261]-267) and index.
650 0 ▼a Image processing.
650 0 ▼a Machine learning.
650 0 ▼a Computer vision.
700 1 0 ▼a Lee, Sungkee, ▼d 1956-.

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 006.37 B575g 등록번호 121018982 도서상태 대출가능 반납예정일 예약 서비스 B M
No. 2 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 006.37 B575g 등록번호 121162459 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

저자소개

Bir Bhanu(지은이)

Sungkee Lee(지은이)

정보제공 : Aladin

목차


CONTENTS
LIST OF FIGURES = Ⅸ
PREFACE = XVII
1 INTRODUCTION = 1
 1.1 Definition of Image Segmentation = 1
 1.2 Characteristics of the Image Segmentation Problem = 2
 1.3 Parameter Selection = 4
 1.4 Multi - Level Vision and Image Segmentation = 7
 1.5 Adaptive Image Segmentation = 9
 1.6 Outline of this Book = 12
2 IMAGE SEGMENTATION TECHNIQUES = 15
 2.1 Edge Detection = 15
 2.2 Region Splitting and Region Glowing = 16
 2.3 The Phoenix Image Segmentation Algorithm = 18
3 SEGMENTATION AS AN OPTIMIZATION PROBLEM = 25
 3.1 Representation of Segmentation Quality = 25
 3.2 Selection of an Optimization Technique = 28
 3.3 Genetic Algorithms for Optimization = 31
4 BASELINE ADAPTIVE IMAGE SEGMENTATION USING A GENETIC ALGORITHM = 39
 4.1 Self - Optimizing Adaptive Image Segmentation System = 39
 4.2 Image Characteristics = 41
 4.3 Image Distance Measure = 44
 4.4 Genetic Learning System = 46
 4.5 Image Segmentation Algorithm = 50
 4.6 Global and Local Segmentation Evaluation = 52
 4.7 Adaptive Image Segmentation Algorithm = 58
5 BASIC EXPERIMENTAL RESULTS - INDOOR IMAGERY = 61
 5.1 Indoor Imagery Experiment = 61
 5.2 Training Experiment = 76
 5.3 Testing Experiment = 96
 5.4 Comparison of the Adaptive Image Segmentation with Other Techniques in Computer Vision = 106
6 BASIC EXPERIMENTAL RESULTS - OUTDOOR IMAGERY = 109
 6.1 Outdoor Imagery Experiments = 109
 6.2 Training Experiments = 133
 6.3 Testing Experiments = 155
 6.4 Comparison of the Adaptive Image Segmentation with Other Techniques in Computer Vision = 177
7 EVALUATING THE EFFECTIVENESS OF THE BASELINE TECHNIQUE - FURTHER EXPERIMENTS = 183
 7.1 Comparison of the Adaptive System with Random Search = 183
 7.2 Effectiveness of the Reproduction and Crossover Operators = 186
 7.3 Demonstration of the Learning Behavior = 188
8 HYBRID SEARCH SCHEME FOR ADAPTIVE IMAGE SEGMENT = 195
 8.1 Integrating Genetic Algorithm and Hill Climbing = 195
 8.2 Experimental Results = 199
9 SIMULTANEOUS OPTIMIZATION OF GLOBAL AND LOCAL EVALUATION MEASURES = 215
 9.1 Multiobjective Optimization with Genetic Algorithm = 216
 9.2 Adaptive Image Segmentation Using Multiobjective Optimization = 218
 9.3 Experimental Results = 220
10 SUMMARY = 255
REFERENCES = 261
INDEX = 269


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