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Time-Varying Image Processing and Moving Object Recognition : Proceedings of the 4th International Workshop Florence, Italy, June 10-11, 1993

By: Cappellini, V.
Material type: TextTextSeries: eBooks on Demand.Publisher: Burlington : Elsevier Science, 2013Description: 1 online resource (444 p.).ISBN: 9781483290256.Subject(s): Image processing -- Digital techniques -- Congresses | Image processing -- Digital techniques | Optical pattern recognition -- Congresses | Optical pattern recognitionGenre/Form: Electronic books.Additional physical formats: Print version:: Time-Varying Image Processing and Moving Object Recognition : Proceedings of the 4th International Workshop Florence, Italy, June 10-11, 1993DDC classification: 621.367 Online resources: Click here to view this ebook.
Contents:
Front Cover; Time-Varying Image Processing and Moving Object Recognition, 3; Copyright Page; Preface; Table of Contents; PART A: DIGITAL PROCESSING METHODS AND TECHNIQUES; Chapter 1. Fast Approximate Calculation of the Two-Dimensional Discrete Fourier Transform; 1. INTRODUCTION; 2. POLYPHASE DECOMPOSITION OF 2-D SEQUENCES AND ITS GENERALIZATION; 3. EFFICIENT APPROXIMATE 2-0 DFT COMPUTATION; 4. AN IMAGE PROCESSING APPLICATION; 5. CONCLUDING REMARKS; Acknowledgments; References; Chapter 2. A constant-geometry multidimensional FFT; 1. Introduction; 2. Background and problem statement
3. A parallel/sequential M-D Cooley-Tukey FFT4. Constant-geometry characteristic; Acknowledgement; References; Chapter 3. Estimation of the Measurement Covariance Matrix in a Kaiman Filter; 1 INTRODUCTION; 2 OVERVIEW OF THE KALMAN FILTER; 3 THE MEASUREMENT UNCERTAINTY; 4 ESTIMATION OF THE MEASUREMENT COVARIANCE MATRIX; 5 EXPERIMENTAL RESULTS; 6 CONCLUSION; REFERENCES; Chapter 4. Real-Time Computation of Statistical Moments on Binary Images UsingBlock Representation; 1. INTRODUCTION; 2. BLOCK REPRESENTATION; 3. GEOMETRICAL MOMENTS; 4. COMPUTATIONAL COMPLEXITY; 5. CONCLUSIONS; REFERENCES
Chapter 5. Reducing segmentation errors through iterative region merging1.INTRODUCTION; 2. IMAGE MODEL , SEGMENTATION ERRORS, AND SIGNAL-TO-NOISE RATIO; 3. HISTOGRAM THRESHOLDING ERRORS; 4. REGION-GROWING ERRORS; 5. ITERATIVE REGION-MERGING APPROACH; 6. CONCLUSIONS; REFERENCES; PART Β: PATTERN RECOGNITION; Chapter 6. Hypergraph Based Feature Matching in a Sequence of Range Images; Abstract; 1 Introduction; 2 Hypergraph Representation; 3 The Matching Procedure; 4 Results; 5 Conclusion; Acknowledgments; References; Chapter 7. A Geometrical Correlation Function for Shape Recognition
1. INTRODUCTION2. GEOMETRICAL CORRELATION FUNCTIONS (GCFs); 3. SHAPE-RECOGNITION BASED ON THE GCF; 4. EXPERIMENTAL RESULTS; 5. SUMMARY; REFERENCES; Chapter 8. Spotting Recognition of Human Gestures from Motion Images; 1. INTRODUCTION; 2. SYSTEM STRUCTURE; 3. FEATURE EXTRACTION; 4. STANDARD SEQUENCE PATTERN; 5. SPOTTING RECOGNITION; 6. EXPERIMENTS; 7. CONSIDERATION; 8. CONCLUSION; ACKNOWLEDGEMENTS; REFERENCES; PART C: IMAGE RESTORATION; Chapter 9. Motion-compensated filtering of noisy image sequences; 1. INTRODUCTION; 2. CLASSIFICATION OF METHODS; 3. NON MOTION-COMPENSATED TECHNIQUES
4. TECHNIQUES USING REGULAR MOTION ESTIMATION5. TECHNIQUES USING NOISE ROBUST MOTION ESTIMATION; 6. FUTURE DEVELOPMENTS; 7. CONCLUSIONS; REFERENCES; Chapter 10. Even-median filters for noisy image restoration; 1. INTRODUCTION; 2. EVEN MEDIAN FILTERS; 3. DUAL-CHANNEL ITERATIVE SCHEME; 4. EXPERIMENTAL RESULTS AND COMPARISONS; 5. CONCLUDING REMARKS; REFERENCES; Chapter 11. Global Probabilistic Reinforcement of Straight Segments; 1. INTRODUCTION; 2. DESCRIPTION OF THE APPROACH; 3. DISTRIBUTED PROBABILISTIC INFERENCE; 4. RESULTS; 5. CONCLUSIONS; 6. ACKNOWLEDGEMENTS; 7. REFERENCES
PART D: IMPLEMENTATION TECHNIQUES
Summary: In the area of Digital Image Processing the new area of ""Time-Varying Image Processing and Moving Oject Recognition"" is contributing to impressive advances in several fields. Presented in this volume are new digital image processing and recognition methods, implementation techniques and advanced applications such as television, remote sensing, biomedicine, traffic, inspection, and robotics. New approaches (such as digital transforms, neural networks) for solving 2-D and 3-D problems are described. Many papers concentrate on motion estimation and recognition i.e. tracking of moving objects. O
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Front Cover; Time-Varying Image Processing and Moving Object Recognition, 3; Copyright Page; Preface; Table of Contents; PART A: DIGITAL PROCESSING METHODS AND TECHNIQUES; Chapter 1. Fast Approximate Calculation of the Two-Dimensional Discrete Fourier Transform; 1. INTRODUCTION; 2. POLYPHASE DECOMPOSITION OF 2-D SEQUENCES AND ITS GENERALIZATION; 3. EFFICIENT APPROXIMATE 2-0 DFT COMPUTATION; 4. AN IMAGE PROCESSING APPLICATION; 5. CONCLUDING REMARKS; Acknowledgments; References; Chapter 2. A constant-geometry multidimensional FFT; 1. Introduction; 2. Background and problem statement

3. A parallel/sequential M-D Cooley-Tukey FFT4. Constant-geometry characteristic; Acknowledgement; References; Chapter 3. Estimation of the Measurement Covariance Matrix in a Kaiman Filter; 1 INTRODUCTION; 2 OVERVIEW OF THE KALMAN FILTER; 3 THE MEASUREMENT UNCERTAINTY; 4 ESTIMATION OF THE MEASUREMENT COVARIANCE MATRIX; 5 EXPERIMENTAL RESULTS; 6 CONCLUSION; REFERENCES; Chapter 4. Real-Time Computation of Statistical Moments on Binary Images UsingBlock Representation; 1. INTRODUCTION; 2. BLOCK REPRESENTATION; 3. GEOMETRICAL MOMENTS; 4. COMPUTATIONAL COMPLEXITY; 5. CONCLUSIONS; REFERENCES

Chapter 5. Reducing segmentation errors through iterative region merging1.INTRODUCTION; 2. IMAGE MODEL , SEGMENTATION ERRORS, AND SIGNAL-TO-NOISE RATIO; 3. HISTOGRAM THRESHOLDING ERRORS; 4. REGION-GROWING ERRORS; 5. ITERATIVE REGION-MERGING APPROACH; 6. CONCLUSIONS; REFERENCES; PART Β: PATTERN RECOGNITION; Chapter 6. Hypergraph Based Feature Matching in a Sequence of Range Images; Abstract; 1 Introduction; 2 Hypergraph Representation; 3 The Matching Procedure; 4 Results; 5 Conclusion; Acknowledgments; References; Chapter 7. A Geometrical Correlation Function for Shape Recognition

1. INTRODUCTION2. GEOMETRICAL CORRELATION FUNCTIONS (GCFs); 3. SHAPE-RECOGNITION BASED ON THE GCF; 4. EXPERIMENTAL RESULTS; 5. SUMMARY; REFERENCES; Chapter 8. Spotting Recognition of Human Gestures from Motion Images; 1. INTRODUCTION; 2. SYSTEM STRUCTURE; 3. FEATURE EXTRACTION; 4. STANDARD SEQUENCE PATTERN; 5. SPOTTING RECOGNITION; 6. EXPERIMENTS; 7. CONSIDERATION; 8. CONCLUSION; ACKNOWLEDGEMENTS; REFERENCES; PART C: IMAGE RESTORATION; Chapter 9. Motion-compensated filtering of noisy image sequences; 1. INTRODUCTION; 2. CLASSIFICATION OF METHODS; 3. NON MOTION-COMPENSATED TECHNIQUES

4. TECHNIQUES USING REGULAR MOTION ESTIMATION5. TECHNIQUES USING NOISE ROBUST MOTION ESTIMATION; 6. FUTURE DEVELOPMENTS; 7. CONCLUSIONS; REFERENCES; Chapter 10. Even-median filters for noisy image restoration; 1. INTRODUCTION; 2. EVEN MEDIAN FILTERS; 3. DUAL-CHANNEL ITERATIVE SCHEME; 4. EXPERIMENTAL RESULTS AND COMPARISONS; 5. CONCLUDING REMARKS; REFERENCES; Chapter 11. Global Probabilistic Reinforcement of Straight Segments; 1. INTRODUCTION; 2. DESCRIPTION OF THE APPROACH; 3. DISTRIBUTED PROBABILISTIC INFERENCE; 4. RESULTS; 5. CONCLUSIONS; 6. ACKNOWLEDGEMENTS; 7. REFERENCES

PART D: IMPLEMENTATION TECHNIQUES

In the area of Digital Image Processing the new area of ""Time-Varying Image Processing and Moving Oject Recognition"" is contributing to impressive advances in several fields. Presented in this volume are new digital image processing and recognition methods, implementation techniques and advanced applications such as television, remote sensing, biomedicine, traffic, inspection, and robotics. New approaches (such as digital transforms, neural networks) for solving 2-D and 3-D problems are described. Many papers concentrate on motion estimation and recognition i.e. tracking of moving objects. O

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