Accuracy of Rotation Invariant Moments for Image Analysis

Accuracy of Rotation Invariant Moments for Image Analysis
Author: Rahul Upneja
Publisher: LAP Lambert Academic Publishing
Total Pages: 88
Release: 2014-03
Genre:
ISBN: 9783659273988

Image processing has become a critical component in Engineering and technology and has numerous applications ranging from nanotechnologies to the digital communication technologies. This book is about the problem of accurate computation of orthogonal rotation invariant moments. The moments and orthogonal polynomials are classical concepts in mathematical analysis due to its attractive properties. This book gives excellent overview of the various image moments. Several new techniques to increase the accuracy and efficiency of moment descriptors are proposed. We utilize these results for solving the problem of reconstruction of images from orthogonal moments. The proposed method provides much improved accuracy of rotation invariant moments which provide very accurate reconstructed images, numerical stability and invariance.

Radial Moments for Invariant Image Analysis

Radial Moments for Invariant Image Analysis
Author: Urmila Samanta
Publisher:
Total Pages: 400
Release: 2013
Genre:
ISBN:

Zernike moments are sets of mathematical quantities that uniquely characterize an image. It is known that they are invariant under rotation and reflection and robust to noise. In this thesis several other algorithms have been used to calculate these moments. The intent of this thesis is: 1. to use the classical method and the algorithms to reconstruct an image using Zernike moments and study their accuracy and 2. to examine if the invariance and noise insensitivity property of the calculated Zernike moments are upheld by these procedures. It is found that the constructed images using these algorithms do not resemble the original image. This prevents us from carrying out further study of these algorithms. The classical method has been successfully used to reconstruct an image when the height and width are equal. The classical method is also shown to be invariant under rotation and reflection and robust to Poisson noise. xxxvii.

Image Analysis and Recognition

Image Analysis and Recognition
Author: Mohamed Kamel
Publisher: Springer Science & Business Media
Total Pages: 977
Release: 2009-07-07
Genre: Computers
ISBN: 3642026117

This book constitutes the refereed proceedings of the 6th International Conference on Image Analysis and Recognition, ICIAR 2009, held in Halifax, Canada, in July 2009. The 93 revised full papers presented were carefully reviewed and selected from 164 submissions. The papers are organized in topical sections on image and video processing and analysis; image segmentation; image and video retrieval and indexing; pattern analysis and recognition; biometrics face recognition; shape analysis; motion analysis and tracking; 3D image analysis; biomedical image analysis; document analysis and applications.

Proceedings of 2nd International Conference on Computer Vision & Image Processing

Proceedings of 2nd International Conference on Computer Vision & Image Processing
Author: Bidyut B. Chaudhuri
Publisher: Springer
Total Pages: 427
Release: 2018-04-11
Genre: Technology & Engineering
ISBN: 9811078955

The book provides insights into the Second International Conference on Computer Vision & Image Processing (CVIP-2017) organized by Department of Computer Science and Engineering of Indian Institute of Technology Roorkee. The book presents technological progress and research outcomes in the area of image processing and computer vision. The topics covered in this book are image/video processing and analysis; image/video formation and display; image/video filtering, restoration, enhancement and super-resolution; image/video coding and transmission; image/video storage, retrieval and authentication; image/video quality; transform-based and multi-resolution image/video analysis; biological and perceptual models for image/video processing; machine learning in image/video analysis; probability and uncertainty handling for image/video processing; motion and tracking; segmentation and recognition; shape, structure and stereo.

Hybrid Metaheuristics for Image Analysis

Hybrid Metaheuristics for Image Analysis
Author: Siddhartha Bhattacharyya
Publisher: Springer
Total Pages: 263
Release: 2018-07-30
Genre: Computers
ISBN: 3319776258

This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization. The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.

Recent Advances in Computer Vision

Recent Advances in Computer Vision
Author: Mahmoud Hassaballah
Publisher: Springer
Total Pages: 425
Release: 2018-12-14
Genre: Technology & Engineering
ISBN: 3030030008

This book presents a collection of high-quality research by leading experts in computer vision and its applications. Each of the 16 chapters can be read independently and discusses the principles of a specific topic, reviews up-to-date techniques, presents outcomes, and highlights the challenges and future directions. As such the book explores the latest trends in fashion creative processes, facial features detection, visual odometry, transfer learning, face recognition, feature description, plankton and scene classification, video face alignment, video searching, and object segmentation. It is intended for postgraduate students, researchers, scholars and developers who are interested in computer vision and connected research disciplines, and is also suitable for senior undergraduate students who are taking advanced courses in related topics. However, it is also provides a valuable reference resource for practitioners from industry who want to keep abreast of recent developments in this dynamic, exciting and profitable research field.

Recent Trends in Image Processing and Pattern Recognition

Recent Trends in Image Processing and Pattern Recognition
Author: K. C. Santosh
Publisher: Springer Nature
Total Pages: 555
Release: 2021-02-25
Genre: Computers
ISBN: 9811605076

This two-volume set constitutes the refereed proceedings of the Third International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2020, held in Aurangabad, India, in January 2020. The 78 revised full papers presented were carefully reviewed and selected from 329 submissions. The papers are organized in topical sections in the two volumes. Part I: Computer vision and applications; Data science and machine learning; Document understanding and Recognition. Part II: Healthcare informatics and medical imaging; Image analysis and recognition; Signal processing and pattern recognition; Image and signal processing in Agriculture.

Moments and Moment Invariants in Pattern Recognition

Moments and Moment Invariants in Pattern Recognition
Author: Jan Flusser
Publisher: John Wiley & Sons
Total Pages: 312
Release: 2009-11-04
Genre: Technology & Engineering
ISBN: 9780470684764

Moments as projections of an image’s intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments. Considers invariants to traditional transforms – translation, rotation, scaling, and affine transform - from a new point of view, which offers new possibilities of designing optimal sets of invariants. Reviews and extends a recent field of invariants with respect to convolution/blurring. Introduces implicit moment invariants as a tool for recognizing elastically deformed objects. Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments. Offers comprehensive advice on the construction of various invariants illustrated with practical examples. Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest.

2D and 3D Image Analysis by Moments

2D and 3D Image Analysis by Moments
Author: Jan Flusser
Publisher: John Wiley & Sons
Total Pages: 555
Release: 2016-12-19
Genre: Technology & Engineering
ISBN: 1119039355

Presents recent significant and rapid development in the field of 2D and 3D image analysis 2D and 3D Image Analysis by Moments, is a unique compendium of moment-based image analysis which includes traditional methods and also reflects the latest development of the field. The book presents a survey of 2D and 3D moment invariants with respect to similarity and affine spatial transformations and to image blurring and smoothing by various filters. The book comprehensively describes the mathematical background and theorems about the invariants but a large part is also devoted to practical usage of moments. Applications from various fields of computer vision, remote sensing, medical imaging, image retrieval, watermarking, and forensic analysis are demonstrated. Attention is also paid to efficient algorithms of moment computation. Key features: Presents a systematic overview of moment-based features used in 2D and 3D image analysis. Demonstrates invariant properties of moments with respect to various spatial and intensity transformations. Reviews and compares several orthogonal polynomials and respective moments. Describes efficient numerical algorithms for moment computation. It is a "classroom ready" textbook with a self-contained introduction to classifier design. The accompanying website contains around 300 lecture slides, Matlab codes, complete lists of the invariants, test images, and other supplementary material. 2D and 3D Image Analysis by Moments, is ideal for mathematicians, computer scientists, engineers, software developers, and Ph.D students involved in image analysis and recognition. Due to the addition of two introductory chapters on classifier design, the book may also serve as a self-contained textbook for graduate university courses on object recognition.

Concise Computer Vision

Concise Computer Vision
Author: Reinhard Klette
Publisher: Springer Science & Business Media
Total Pages: 441
Release: 2014-01-04
Genre: Computers
ISBN: 1447163206

This textbook provides an accessible general introduction to the essential topics in computer vision. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter. Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an image; explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an image; introduces optic flow for representing dense motion and various topics in sparse motion analysis; describes special approaches for image binarization and segmentation of still images or video frames; examines the basic components of a computer vision system; reviews different techniques for vision-based 3D shape reconstruction; includes a discussion of stereo matchers and the phase-congruency model for image features; presents an introduction into classification and learning.