A two-stage framework for polygon retrieval.

by Tung Lun Hsing.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 80-84).Abstract --- p.iAcknowledgement --- p.iiChapter 1 --- Introduction --- p.1Chapter 2 --- Literature Survey --- p.8Chapter 2.1 --- The Freeman Chain Code Approach --- p.8Chapter 2.2 --- The Moment Approach --- p.10Chapter 2.3 --- The Rectangular Cover Approach --- p.12Chapter 2.4 --- The Potential-Based Approach --- p.15Chapter 2.5 --- The Normalized Coordinate System Approach --- p.17Chapter 2.6 --- The Hausdorff Distance Method --- p.20Chapter 2.7 --- The PCA Approach --- p.22Chapter 3 --- Binary Shape Descriptor --- p.26Chapter 3.1 --- Basic idea --- p.26Chapter 3.2 --- Standardized Binary String Descriptor --- p.27Chapter 3.3 --- Number of equivalent classes for n-gons --- p.28Chapter 4 --- The Two-Stage Framework --- p.30Chapter 5 --- Multi-Resolution Area Matching --- p.33Chapter 5.1 --- The idea --- p.33Chapter 5.2 --- Computing MRAI --- p.34Chapter 5.3 --- Measuring similarity using MRAI --- p.36Chapter 5.4 --- Query processing using MRAM --- p.38Chapter 5.5 --- Characteristics and Discussion --- p.40Chapter 6 --- Circular Error Bound and Minimum Circular Error Bound --- p.41Chapter 6.1 --- Polygon Matching using Circular Error Bound --- p.41Chapter 6.1.1 --- Translation --- p.43Chapter 6.1.2 --- Translation and uniform scaling in x-axis and y-axis directions --- p.45Chapter 6.1.3 --- Translation and independent scaling in x-axis and y-axis directions --- p.47Chapter 6.2 --- Minimum Circular Error Bound --- p.48Chapter 6.3 --- Characteristics --- p.49Chapter 7 --- Experimental Results --- p.50Chapter 7.1 --- Setup --- p.50Chapter 7.1.1 --- Polygon generation --- p.51Chapter 7.1.2 --- Database construction --- p.52Chapter 7.1.3 --- Query processing --- p.54Chapter 7.2 --- Running time comparison --- p.55Chapter 7.2.1 --- Experiment I --- p.55Chapter 7.2.2 --- Experiment II --- p.58Chapter 7.2.3 --- Experiment III --- p.60Chapter 7.3 --- Visual ranking comparison --- p.61Chapter 7.3.1 --- Experiment I --- p.61Chapter 7.3.2 --- Experiment II --- p.62Chapter 7.3.3 --- Experiment III --- p.63Chapter 7.3.4 --- Conclusion on visual ranking experiments --- p.66Chapter 8 --- Discussion --- p.68Chapter 8.1 --- N-ary Shape Descriptor --- p.68Chapter 8.2 --- Distribution of polygon equivalent classes --- p.69Chapter 8.3 --- Comparing polygons with different number of vertices --- p.72Chapter 8.4 --- Relaxation of assumptions --- p.73Chapter 8.4.1 --- Non-degenerate --- p.74Chapter 8.4.2 --- Simple --- p.74Chapter 8.4.3 --- Closed --- p.76Chapter 9 --- Conclusion --- p.78Bibliography --- p.8

Multi-Resolution Area Matching

In this paper we present a general and robust approach to the problem of close-range partial 3D reconstruction of ob-jects from multi-resolution texture matching. The method is based on the progressive refininement of a parametric sur-face, which is described using an increasing number of ra-dial functions. 1

c ○ 2000 Kluwer Academic Publishers. Manufactured in The Netherlands. A Two-Stage Framework for Polygon Retrieval

Abstract. We propose a two-stage framework for polygon retrieval which incorporates both qualitative and quantitative measures of polygons in the first and second stage respectively. The first stage uses Binary Shape Descriptor as a mean to prune the search space. The second stage uses any available polygon matching and similarity measuring technique to compare model polygons with the target polygon. This two-stage framework uses a combination of model-driven approach and data-driven approach. It is more efficient than model-driven approach since it reduces the number of polygons needed to be compared. By using binary string as index, it also avoids the difficulty and inefficiency of manipulating complex multi-dimensional index structure. This twostage framework can be incorporated into image database systems for providing query-by-shape facility. We also propose two similarity measures for polygons, namely Multi-Resolution Area Matching and Minimum Circular Error Bound, which can be used in the second stage of the two-stage framework. We compare these two techniques with the Hausdorff Distance method and the Normalized Coordinate System method. Our experiments show that Multi-Resolution Area Matching technique is more efficient than the two methods and Minimum Circular Error Bound technique produces better polygon similarity measure than the two methods