A survey of shape analysis techniques

PART I: FUNDAMENTALS. 1 INTRODUCTION. 1.1 The World of Signals. 1.2 Digital Image Processing. 1.3 Elements of an Image Processing System. Appendix 1.A Selected List of Books on Image Processing and Computer Vision from Year 2000. References. 2 MATHEMATICAL PRELIMINARIES. 2.1 Laplace Transform. 2.2 Fourier Transform. 2.3 Z-Transform. 2.4 Cosine Transform. 2.5 Wavelet Transform. 3 IMAGE ENHANCEMENT. 3.1 Grayscale Transformation. 3.2 Piecewise Linear Transformation. 3.3 Bit Plane Slicing. 3.4 Histogram Equalization. 3.5 Histogram Specification. 3.6 Enhancement by Arithmetic Operations. 3.7 Smoothing Filter. 3.8 Sharpening Filter. 3.9 Image Blur Types and Quality Measures. 4 MATHEMATICAL MORPHOLOGY. 4.1 Binary Morphology. 4.2 Opening and Closing. 4.3 Hit-or-Miss Transform. 4.4 Grayscale Morphology. 4.5 Basic Morphological Algorithms. 4.6 Morphological Filters. 5 IMAGE SEGMENTATION. 5.1 Thresholding. 5.2 Object (Component) Labeling. 5.3 Locating Object Contours by the Snake Model. 5.4 Edge Operators. 5.5 Edge Linking by Adaptive Mathematical Morphology. 5.6 Automatic Seeded Region Growing. 5.7 A Top-Down Region Dividing Approach. 6 DISTANCE TRANSFORMATION AND SHORTEST PATH PLANNING. 6.1 General Concept. 6.2 Distance Transformation by Mathematical Morphology. 6.3 Approximation of Euclidean Distance. 6.4 Decomposition of Distance Structuring Element. 6.5 The 3D Euclidean Distance. 6.6 The Acquiring Approaches. 6.7 The Deriving Approaches. 6.8 The Shortest Path Planning. 6.9 Forward and Backward Chain Codes for Motion Planning. 6.10 A Few Examples. 7 IMAGE REPRESENTATION AND DESCRIPTION. 7.1 Run-Length Coding. 7.2 Binary Tree and Quadtree. 7.3 Contour Representation. 7.4 Skeletonization by Thinning. 7.5 Medial Axis Transformation. 7.6 Object Representation and Tolerance. 8 FEATURE EXTRACTION. 8.1 Fourier Descriptor and Moment Invariants. 8.2 Shape Number and Hierarchical Features. 8.3 Corner Detection. 8.4 Hough Transform. 8.5 Principal Component Analysis. 8.6 Linear Discriminate Analysis. 8.7 Feature Reduction in Input and Feature Spaces. 9 PATTERN RECOGNITION. 9.1 The Unsupervised Clustering Algorithm. 9.2 Bayes Classifier. 9.3 Support Vector Machine. 9.4 Neural Networks. 9.5 The Adaptive Resonance Theory Network. 9.6 Fuzzy Sets in Image Analysis. PART II: APPLICATIONS. 10 FACE IMAGE PROCESSING AND ANALYSIS. 10.1 Face and Facial Feature Extraction. 10.2 Extraction of Head and Face Boundaries and Facial Features. 10.3 Recognizing Facial Action Units. 10.4 Facial Expression Recognition in JAFFE Database. 11 DOCUMENT IMAGE PROCESSING AND CLASSIFICATION. 11.1 Block Segmentation and Classification. 11.2 Rule-Based Character Recognition System. 11.3 Logo Identification. 11.4 Fuzzy Typographical Analysis for Character Preclassification. 11.5 Fuzzy Model for Character Classification. 12 IMAGE WATERMARKING. 12.1 Watermarking Classification. 12.2 Spatial Domain Watermarking. 12.3 Frequency-Domain Watermarking. 12.4 Fragile Watermark. 12.5 Robust Watermark. 12.6 Combinational Domain Digital Watermarking. 13 IMAGE STEGANOGRAPHY. 13.1 Types of Steganography. 13.2 Applications of Steganography. 13.3 Embedding Security and Imperceptibility. 13.4 Examples of Steganography Software. 13.5 Genetic Algorithm-Based Steganography. 14 SOLAR IMAGE PROCESSING AND ANALYSIS. 14.1 Automatic Extraction of Filaments. 14.2 Solar Flare Detection. 14.3 Solar Corona Mass Ejection Detection. INDEX.

Image Processing and Pattern Recognition: Fundamentals and Techniques

Various systems and methods are provided that display various interactive user interfaces containing interactive maps. The user may use the interactive map to perform searches for data objects, toggle different layers associated with different types of objects for display, generate heatmaps based upon a grid and/or data object shapes, copy data between different interactive maps, and/or define filters to filter the displayed data. In response to user interaction with the map at a client system, tile layers are generated using server-side components, assembled into map tiles, and transmitted to client-side components to be displayed to the user. The tile layers may include a base tile layer, vector tile layer, selection tile layer, and inactive tile layer.

Interactive geospatial map

A system of one or more computing devices is utilized for, among other purposes, creating a template-driven search interface and conducting searches thereon In an embodiment, the system comprises: a template repository; search templates in the template repository, the search templates comprising at least: field specification data that specify search interface fields for obtaining search input data, and query specification data that specify how to generate structured queries based on the search input data obtained for the one or more of the search interface fields; a search field generator that generates search fields indicated by the field specification data; a template loading module, coupled to the template repository, that identifies available search templates in the template repository; and a search interface generator, coupled to the search field generator and template loading module, that generates different search interfaces depending on which template is selected

Simple web search

Solution approaches to irregular nesting problems

This paper gives a complete solution to the polygon containment problem under translation and other related problems for all kinds of two dimensional regions. The solution is achieved in three steps. First, it is shown that the containment and the related problems can be directly mapped to Minkowski decomposition and addition problems. Minkowski decomposition, which is intrinsically a geometric problem, is then reformulated in terms of set operations and set theoretic tools are used to reduce the computational complexity of the problem. Finally, a new technique, termed as decomposition boundary tracing technique, is devised and employed for the solution of the decomposition problem. This new technique brings out a unified algorithmic approach to solve all kinds of decomposition problems in a two dimensional space, and thereby the containment problem in its entirety.

A solution of polygon containment, spatial planning, and other related problems using minkowski operations

Using two new shape operators called Minkowski addition and decomposition operators, a simple shape model is presented. Mathematical characteristics of these operators are explored in some detail, with the aim of eventually arriving at a formal theory of shape description. A few application areas of the shape model, particularly some important uses of the shape operators are briefly mentioned.

Pijush K. Ghosh

Papers

A solution of polygon containment, spatial planning, and other related problems using minkowski operations

A mathematical model for shape description using Minkowski operators