Psychological Processes in Pattern Recognition

Psychological Processes in Pattern Recognition describes information-processing models of pattern recognition. This book is organized into five parts encompassing 11 chapters that particularly focus on visual pattern recognition and the many issues relevant to a more general theory of pattern recognition.

The first three parts cover the representation, temporal effects, and memory codes of pattern recognition. These parts include the features, templates, schemata, and structural descriptions of information processing models. The principles of parallel matching, iconic storage, and the components and networks of memory codes are also considered. The remaining two parts look into the perceptual classification and response selection of pattern recognition. These parts specifically tackle the development of probability, distance, and recognition models.

This book is intended primarily for psychologists, graduate students, and researchers who are interested in the problems of pattern recognition and human information processing.

Preface

Acknowledgments

I. Introduction

Information-Processing Models

Content and Organization

Part 1. Representation

II. Features, Templates, and Schemata

Features

Concrete Images

Schema Theory

Summary

III. Structural Descriptions

Spatial Relations and Development

Structural Models in Artificial Intelligence

Structural Models in Psychology

Summary

Part 2. Temporal Effects

IV. Serial or Parallel Matching

Multidimensional Matching

Sternberg's Theory

Neisser's Theory

Identification and Classification

Summary

V. Iconic Storage

Evidence for Iconic Storage

Serial Scan

Parallel Scan

Visual Masking

Summary

Part 3. Memory Codes

VI. Visual and Verbal Codes

Matching Names and Images

Visual Representations in Long-Term Memory

Verbal Descriptions in Recognition and Recall

Accuracy of Visual Images

Summary

VII. Memory Models: Components and Networks

Multicomponent Models

Applications of Component Models

Network Models

Summary

Part 4. Perceptual Classification

VIII. Probability Models

Probabilistic or Deterministic Decision Rules

Discriminant Analysis

Summation of Cue Validities

Summary

IX. Distance Models

Classification and Attention

Saliency and Validity

Categorization Models

Additivity

Summary

Part 5. Response Selection

X. Set and Bias

Effects of Set

Encoding Strategies

Word Recognition and Response Bias

Summary

XI. Recognition Models

Choice Models

Pattern Similarities

Analysis-by-Synthesis

Summary

XII. Overview

References

Index