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Author: Robert M. Haralick
Publisher: Springer Science & Business Media
ISBN: 3642820174
Category : Computers
Languages : en
Pages : 468
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Book Description
This volume is the collection of lectures and presentations of the NATO AS! On Pictorial Data Analysis, held August 1-12, 1982 in the beautiful chateau de Bonas, Bonas France. The director of the AS! was Robert M. Haralick and the Co-director was Stefano Levialdi. The papers in the book are arranged in two sections first theory and general prinicples and then applications. Local computations play a central role in image processing both when a traditional computer is used and when parallel machines are used for improving image throughput. Levialdi reviews such neighborhood operators. Hung and Kasvand discuss a line thinning application which involves detection of critical points on chain encoded data. Most low level image processing has been done using the digital raster as the basic data structure. Within the last few years many of these basic algorithms have been developed for the quadtree data structure. The quadtree permits easier access to certain kinds of spatial adjacency relationships in a variable resolution context. Rosenfeld reviews the properties of these representations and their uses in image segmentation and property measurement. Besslich discusses an expanded form of an invertible quadtree representation which permits a multiprocessor execution. Gisolfi and Vitulano discuss the C-matrix and C-filtering technique for image and texture feature extraction. O'mara et.al. discuss the application of Codel numbers to image feature extraction. Kropatsch discusses an image segmentation technique which permits the effective use of a variety of different kinds of segmentation techniques.
Author: Robert M. Haralick
Publisher: Springer Science & Business Media
ISBN: 3642820174
Category : Computers
Languages : en
Pages : 468
Get Book Here
Book Description
This volume is the collection of lectures and presentations of the NATO AS! On Pictorial Data Analysis, held August 1-12, 1982 in the beautiful chateau de Bonas, Bonas France. The director of the AS! was Robert M. Haralick and the Co-director was Stefano Levialdi. The papers in the book are arranged in two sections first theory and general prinicples and then applications. Local computations play a central role in image processing both when a traditional computer is used and when parallel machines are used for improving image throughput. Levialdi reviews such neighborhood operators. Hung and Kasvand discuss a line thinning application which involves detection of critical points on chain encoded data. Most low level image processing has been done using the digital raster as the basic data structure. Within the last few years many of these basic algorithms have been developed for the quadtree data structure. The quadtree permits easier access to certain kinds of spatial adjacency relationships in a variable resolution context. Rosenfeld reviews the properties of these representations and their uses in image segmentation and property measurement. Besslich discusses an expanded form of an invertible quadtree representation which permits a multiprocessor execution. Gisolfi and Vitulano discuss the C-matrix and C-filtering technique for image and texture feature extraction. O'mara et.al. discuss the application of Codel numbers to image feature extraction. Kropatsch discusses an image segmentation technique which permits the effective use of a variety of different kinds of segmentation techniques.
Author: J. M. Chambers
Publisher: CRC Press
ISBN: 135108920X
Category : Mathematics
Languages : en
Pages : 551
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Book Description
This book present graphical methods for analysing data. Some methods are new and some are old, some require a computer and others only paper and pencil; but they are all powerful data analysis tools. In many situations, a set of data even a large set- can be adequately analysed through graphical methods alone. In most other situations, a few well-chosen graphical displays can significantly enhance numerical statistical analyses.
Author: Kevin J Keen
Publisher: CRC Press
ISBN: 1584880872
Category : Mathematics
Languages : en
Pages : 486
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Book Description
Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools for data visualization and representation. The book considers graphical displays of a single discrete variable, a single continuous variable, and then two or more of each of these. It includes displays and the R code for producing the displays for the dot chart, bar chart, pictographs, stemplot, boxplot, and variations on the quantile-quantile plot. The author discusses nonparametric and parametric density estimation, diagnostic plots for the simple linear regression model, polynomial regression, and locally weighted polynomial regression for producing a smooth curve through data on a scatterplot. The last chapter illustrates visualizing multivariate data with examples using Trellis graphics. Showing how to use graphics to display or summarize data, this text provides best practice guidelines for producing and choosing among graphical displays. It also covers the most effective graphing functions in R. R code is available for download on the book’s website.
Author: BUDD CO MCLEAN VA INFORMATION SCIENCES CENTER.
Publisher:
ISBN:
Category :
Languages : en
Pages : 127
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Book Description
The problem of developing rules for subdividing complex pictures into 'uniform' regions is discussed. Experiments are described in which rules of this type applicable to 'one-dimensional' pictures are derived from an analysis of observers' subdivision preferences. (Author).
Author: S. H. C. DuToit
Publisher: Springer Science & Business Media
ISBN: 1461249503
Category : Mathematics
Languages : en
Pages : 322
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Book Description
Portraying data graphically certainly contributes toward a clearer and more penetrative understanding of data and also makes sophisticated statistical data analyses more marketable. This realization has emerged from many years of experience in teaching students, in research, and especially from engaging in statistical consulting work in a variety of subject fields. Consequently, we were somewhat surprised to discover that a comprehen sive, yet simple presentation of graphical exploratory techniques for the data analyst was not available. Generally books on the subject were either too incomplete, stopping at a histogram or pie chart, or were too technical and specialized and not linked to readily available computer programs. Many of these graphical techniques have furthermore only recently appeared in statis tical journals and are thus not easily accessible to the statistically unsophis ticated data analyst. This book, therefore, attempts to give a sound overview of most of the well-known and widely used methods of analyzing and portraying data graph ically. Throughout the book the emphasis is on exploratory techniques. Real izing the futility of presenting these methods without the necessary computer programs to actually perform them, we endeavored to provide working com puter programs in almost every case. Graphic representations are illustrated throughout by making use of real-life data. Two such data sets are frequently used throughout the text. In realizing the aims set out above we avoided intricate theoretical derivations and explanations but we nevertheless are convinced that this book will be of inestimable value even to a trained statistician.
Author: Martin Theus
Publisher: CRC Press
ISBN: 1420011065
Category : Computers
Languages : en
Pages : 293
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Book Description
Interactive Graphics for Data Analysis: Principles and Examples discusses exploratory data analysis (EDA) and how interactive graphical methods can help gain insights as well as generate new questions and hypotheses from datasets.Fundamentals of Interactive Statistical GraphicsThe first part of the book summarizes principles and methodology, demons
Author: Glenn J. Myatt
Publisher: John Wiley & Sons
ISBN: 0470222808
Category : Mathematics
Languages : en
Pages : 325
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Book Description
A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios. Each method is discussed within the context of a data mining process including defining the problem and deploying the results, and readers are provided with guidance on when and how each method should be used. The related Web site for the series (www.makingsenseofdata.com) provides a hands-on data analysis and data mining experience. Readers wishing to gain more practical experience will benefit from the tutorial section of the book in conjunction with the TraceisTM software, which is freely available online. With its comprehensive collection of advanced data mining methods coupled with tutorials for applications in a range of fields, Making Sense of Data II is an indispensable book for courses on data analysis and data mining at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who are interested in learning how to accomplish effective decision making from data and understanding if data analysis and data mining methods could help their organization.
Author: Nathan Yau
Publisher: John Wiley & Sons
ISBN: 1118654935
Category : Computers
Languages : en
Pages : 8
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Book Description
A fresh look at visualization from the author of Visualize This Whether it's statistical charts, geographic maps, or the snappy graphical statistics you see on your favorite news sites, the art of data graphics or visualization is fast becoming a movement of its own. In Data Points: Visualization That Means Something, author Nathan Yau presents an intriguing complement to his bestseller Visualize This, this time focusing on the graphics side of data analysis. Using examples from art, design, business, statistics, cartography, and online media, he explores both standard-and not so standard-concepts and ideas about illustrating data. Shares intriguing ideas from Nathan Yau, author of Visualize This and creator of flowingdata.com, with over 66,000 subscribers Focuses on visualization, data graphics that help viewers see trends and patterns they might not otherwise see in a table Includes examples from the author's own illustrations, as well as from professionals in statistics, art, design, business, computer science, cartography, and more Examines standard rules across all visualization applications, then explores when and where you can break those rules Create visualizations that register at all levels, with Data Points: Visualization That Means Something.
Author: GEORGE (EDITOR) MICHAEL
Publisher:
ISBN:
Category :
Languages : en
Pages : 105
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Book Description
Author: Edward R. Tufte
Publisher:
ISBN: 9780961392147
Category : Mathematics
Languages : en
Pages : 197
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Book Description
Graphical practice. Theory of data graphics.
