2042582
Pose determination of a cylinder using reprojection transformation
Extracting useful and robust feature points from a cylinder image for 3D pose determination is a relatively difficult task, since there are no feature points or lines on the cylinder. In this study, a key vector from a cylinder image is found to yield a transformation. The cylinder is then ''reprojected'' from the original image to obtain a new image using the transformation. The new image reveals some important features capable of determining the 3D cylinder position robustly. The proposed method can yield an exact and analytical solution without the requirement of using any special marks, extra equipment or assumptions. Additionally, a problem in which both circles on the cylinder are not completely visible due to the viewing angle can be resolved by this method. Finally, experimental results are provided to verify the theory and show the robustness of our method.
42618487
Handwritten Chinese Character Recognition Using Stroke Structural Sequence Code
1822288
Incremental model building of polyhedral objects using structured light
Abstract A vision method using active sensing to construct the complete geometric model of a polyhedral object is presented. The model is constructed incrementally from multiple views. Each view produces a partial object model. Three different methods are described for integrating all the partial models into a final complete model. Theorems regarding the sufficient number of views required and how these views can be set up during the reconstruction process are also given. From theoretical analysis and experimental results, our method is shown to produce an accurate object geometric model, not just an approximate model. Furthermore, it does not rely on a precise object-to-image space transformation. Moreover, the method is fast and robust, since the basic geometric entity it derives is a face instead of a point.
21895291
Determination of feature correspondences in stereo images using a calibration polygon
In this paper, we propose a novel approach to solving the vertex/edge correspondence problem for stereo images. Assume an object is placed on a calibration plate (C-plate) and two perspective views of them are given. The C-plate vertex correspondence, determined by cross-ratios, is used to reduce the search space for determining object vertex/edge correspondence. First, the correspondence of object edges lying on the C-plate (called the object base edges) is considered. This is because the subpolygons obtained from the division of the C-plate by the extended line of each of these base edges are viewpoint invariant, i.e. the cross-ratio of each of their vertices in different images will have equal value. Assume that at least one of the base edges is visible in each image. Since a visible object base edge has to be an object boundary edge in an image, only object boundary edges will be considered for the cross-ratios check for the associated subpolygons as well as other geometric constraint checks in determining the object base vertex/edge correspondence. These geometric constraints include (i) the position of the edges along the boundary of object faces, and (ii) the division of the C-plate vertices by the extended lines of these edges. Based on one of the determined corresponding base edge pairs, the correspondence of all other edges can be determined by constraints similar to (i). Finally, some additional viewpoint invariant measures about the object faces and the C-plates are introduced to resolve the ambiguity problem which may arise for specific viewpoints and some special object shapes. The proposed approach only needs 2-D image data and has no constraint on the number of vertices of an object face. Experimental results are presented for some polyhedral as well as curved objects.
86627129
Identification of business forms using relationships between adjacent frames
This paper proposes a method of using relationships between adjacent frames to identify business forms. First, we use the relations between adjacent frames in the business form to represent each form as two graphs. We then convert these graphs to two 1-D strings, which are used to perform matching. This approach enables forms to be identified quickly, and it places no restrictions on the layout of the business forms.
3177556
A parallel architecture for probabilistic relaxation operations on images
Abstract The design of a parallel architecture for executing probabilistic relaxation operations on two dimensional images is addressed. First of all, the concerned relaxation process is divided into three different parallel operations, i.e. systolic, simultaneous, and pipelined. All these parallel operations are mapped onto a linear array architecture that runs smoothly without any bottleneck in the data flows. The proposed architecture and its components are described. An illustrative running of the relaxation process for an image thresholding application on the architecture is described in some details. The hardware implementation and CAD logic simulation are then given. Finally, performance comparison between the proposed architecture and some existing ones is reported.
28595321
A PTAS for a Disc Covering Problem Using Width-Bounded Separators
In this paper, we study the following disc covering problem: Given a set of discs of various radii on the plane, find a subset of discs to maximize the area covered by exactly one disc. This problem originates from the application in digital halftoning, with the best known approximation factor being 5.83 [2]. We show that if the maximum radius is no more than a constant times the minimum radius, then there exists a polynomial time approximation scheme. Our techniques are based on the width-bounded geometric separator recently developed in [5,6].
701
Common-Face Embeddings of Planar Graphs
Given a planar graph $\Ggg$ and a sequence ${\CC}_1,\ldots,{\CC}_q$, where each ${\CC}_i$ is a family of vertex subsets of $\Ggg$, we wish to find a plane embedding of $\Ggg$, if any exists, such that, for each $i\in\{1,\ldots,q\}$, there is a face Fi in the embedding whose boundary contains at least one vertex from each set in CCi. This problem has applications in the recovery of topological information from geographical data and the design of constrained layouts in VLSI. Let $\inputsize$ be the input size, i.e., the total number of vertices and edges in $\Ggg$ and the families CCi, counting multiplicity. We show that this problem is NP-complete in general. We also show that it is solvable in $O(\inputsize\log \inputsize)$ time for the special case in which, for each input family CCi, each set in CCi induces a connected subgraph of the input graph $\Ggg$. Note that the classical problem of simply finding a planar embedding is a further special case of this case with q=0. Therefore, the processing of the additional constraints CC1, . . .,CCq incurs only a logarithmic factor of overhead.
19262472
Relevance Feedback and Learning in Content-Based Image Search
A major bottleneck in content-based image retrieval (CBIR) systems or search engines is the large gap between low-level image features used to index images and high-level semantic contents of images. One solution to this bottleneck is to apply relevance feedback to refine the query or similarity measures in image search process. In this paper, we first address the key issues involved in relevance feedback of CBIR systems and present a brief overview of a set of commonly used relevance feedback algorithms. Almost all of the previously proposed methods fall well into such framework. We present a framework of relevance feedback and semantic learning in CBIR. In this framework, low-level features and keyword annotations are integrated in image retrieval and in feedback processes to improve the retrieval performance. We have also extended framework to a content-based web image search engine in which hosting web pages are used to collect relevant annotations for images and users' feedback logs are used to refine annotations. A prototype system has developed to evaluate our proposed schemes, and our experimental results indicated that our approach outperforms traditional CBIR system and relevance feedback approaches.
6289519
Second-level buffer cache management
Buffer caches are commonly used in servers to reduce the number of slow disk accesses or network messages. These buffer caches form a multilevel buffer cache hierarchy. In such a hierarchy, second-level buffer caches have different access patterns from first-level buffer caches because accesses to a second-level are actually misses from a first-level. Therefore, commonly used cache management algorithms such as the least recently used (LRU) replacement algorithm that work well for single-level buffer caches may not work well for second-level. We investigate multiple approaches to effectively manage second-level buffer caches. In particular, we report our research results in 1) second-level buffer cache access pattern characterization, 2) a new local algorithm called multi-queue (MQ) that performs better than nine tested alternative algorithms for second-level buffer caches, 3) a set of global algorithms that manage a multilevel buffer cache hierarchy globally and significantly improve second-level buffer cache hit ratios over corresponding local algorithms, and 4) implementation and evaluation of these algorithms in a real storage system connected with commercial database servers (Microsoft SQL server and Oracle) running industrial-strength online transaction processing benchmarks.
1777247
Web-page classification through summarization
Web-page classification is much more difficult than pure-text classification due to a large variety of noisy information embedded in Web pages. In this paper, we propose a new Web-page classification algorithm based on Web summarization for improving the accuracy. We first give empirical evidence that ideal Web-page summaries generated by human editors can indeed improve the performance of Web-page classification algorithms. We then propose a new Web summarization-based classification algorithm and evaluate it along with several other state-of-the-art text summarization algorithms on the LookSmart Web directory. Experimental results show that our proposed summarization-based classification algorithm achieves an approximately 8.8% improvement as compared to pure-text-based classification algorithm. We further introduce an ensemble classifier using the improved summarization algorithm and show that it achieves about 12.9% improvement over pure-text based methods.