David G. Stork

PIXELS & PAINTINGS “The discussion is firmly grounded in established art historical practices, such as close visual analysis and an understanding of artists’ working methods, and real-world examples demonstrate how computer-assisted techniques can complement traditional approaches.” —Dr. Emilie Gordenker, Director of the Van Gogh Museum The pioneering presentation of computer-based image analysis of fine art, forging a dialog between art scholars and the computer vision community In recent years, sophisticated computer vision, graphics, and artificial intelligence algorithms have proven to be increasingly powerful tools in the study of fine art. These methods—some adapted from forensic digital photography and others developed specifically for art—empower a growing number of computer-savvy art scholars, conservators, and historians to answer longstanding questions as well as provide new approaches to the interpretation of art. Pixels & Paintings provides the first and authoritative overview of the broad range of these methods, which extend from image processing of palette, marks, brush strokes, and shapes up through analysis of objects, poses, style, composition, to the computation of simple interpretations of artworks. This book stresses that computer methods for art analysis must always incorporate the cultural contexts appropriate to the art studies at hand—a blend of humanistic and scientific expertise. Describes powerful computer image analysis methods and their application to problems in the history and interpretation of fine artDiscusses some of the art historical lessons and revelations provided by the use of these methodsClarifies the assumptions and applicability of methods and the role of cultural contexts in their useShows how computation can be used to analyze tens of thousands of artworks to reveal trends and anomalies that could not be found by traditional non-computer methods Pixels & Paintings is essential reading for computer image analysts and graphics specialists, conservators, historians, students, psychologists and the general public interested in the study and appreciation of art.

Computer Manual in MATLAB to Accompany Pattern Classification (2ND ed.) Preface. Chapter 1. Introduction to MATLAB. Basic Navigation and Interaction. Scalars, Variables and Basic Arithmetic. Relational and Logical Operators. Lists, Vectors and Matrices. Matrix Multiplication. Vector and Matrix Norms. Determinants, Inverses and Pseudoinverses. Matrix Powers and Exponentials. Eigenvalues and Eigenvectors. Data Analysis. Clearing Variables and Functions. Data Types. Chapter 2. Programming in MATLAB. Scripts. Functions. Flow Control. User Input. Debugging. Data, and File Input and Output. Strings. Operations on Strings. Chapter 3. Classification Toolbox. Loading the Toolbox and Starting MATLAB. Graphical User Interface. Introductory Examples. GUI Controls. Creating Your Own Data Files. Classifying Using the Text-based Interface. Classifier Comparisons. How to Add New Algorithms. Adding a New Feature Selection Algorithm. List of Functions. Appendix: Program Descriptions. References. Index.

The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.

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