Stereo computation is one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results th...
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We describe the design and implementation of an online fingerprint verification system which operates in two stages: (i) minutia extraction and (ii) minutia matching. An improved minutia extraction algorithm that is m...
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We describe the design and implementation of an online fingerprint verification system which operates in two stages: (i) minutia extraction and (ii) minutia matching. An improved minutia extraction algorithm that is much faster and more accurate than our earlier algorithm has been implemented. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between input minutiae and the stored template without resorting to exhaustive search and has the ability to adaptively compensate for the nonlinear deformations and inexact pose transformations between finger prints. The system has been tested on two sets of finger print images captured with inkless scanners. The verification accuracy is found to be over 99% with a 15% reject rate. Typically, a complete fingerprint verification procedure takes, on an average, about 8 seconds on a SPARC 20 workstation. It meets the response time requirements of on-line verification with high accuracy.
Stereo computation is one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results th...
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Stereo computation is one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results that cannot be corrected in subsequent postprocessing stages. In this paper we present a modification of the standard area-based correlation approach so that it can tolerate a significant number of outliers. The approach exhibits a robust behavior not only in the presence of mismatches but also in the case of depth discontinuities. The confidence measure of the correlation and the number of outliers provide two complementary sources of information which, when implemented in a multiresolution framework, result in a robust and efficient method. We present the results of this approach on a number of synthetic and real images.
The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this pa...
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The basic limitations of the current appearance-based matching methods using eigenimages are non-robust estimation of coefficients and inability to cope with problems related to occlusions and segmentation. In this paper we present a new approach which successfully solves these problems. The major novelty of our approach lies in the way how the coefficients of the eigenimages are determined. Instead of computing the coefficients by a projection of the data onto the eigenimages. we extract them by a hvpothesize-and-test paradigm using subsets of image points. Competing hypotheses arc then subject to a selection procedure based on the Minimum Description Length principle. The approach enables us not only lo reject outliers and to deal with occlusions but also to simultaneously use multiple classes of eigenimages.
Control of a computer workstation via face position and facial gesturing would be an important advance for people with hand or body disabilities as well as for all users. Steps toward realization of such a system are ...
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Control of a computer workstation via face position and facial gesturing would be an important advance for people with hand or body disabilities as well as for all users. Steps toward realization of such a system are reported here. A computer system has been developed to track the eyes and the nose of a subject and to compute the direction of the face. Face direction and movement is then used to control the cursor. Test results show that the resulting system is usable, although several improvements are needed.
We propose a new texture-based page segmentation algorithm which automatically extracts the text, halftone, and line-drawing regions from input greyscale document images. This approach utilizes a neural network to tra...
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We propose a new texture-based page segmentation algorithm which automatically extracts the text, halftone, and line-drawing regions from input greyscale document images. This approach utilizes a neural network to train a set of masks which is optimal for discriminating the three main texture classes in the page segmentation problem: halftone, background, and text and line-drawing regions. The test and line-drawing regions are further discriminated based on connectivity analysis. We have applied the algorithm to successfully segment English and Chinese document images. We also demonstrate that the masks can perform language separation (English/Chinese) when appropriately trained.
While the view of constructive and hierarchical vision prevails, the issues of cooperation and competition among individual modules become crucial. These issues are directly related to one of the most important aspect...
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While the view of constructive and hierarchical vision prevails, the issues of cooperation and competition among individual modules become crucial. These issues are directly related to one of the most important aspect...
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ISBN:
(纸本)078031865X
While the view of constructive and hierarchical vision prevails, the issues of cooperation and competition among individual modules become crucial. These issues are directly related to one of the most important aspects in computer vision research: integration. A major source of difficulty in developing a consistent and systematic integration formalism is the heterogeneity existing in modules, in information, and in knowledge. The author exploits, using the central theme of grouping, the homogeneous characteristics in vision problem solving and proposes a general framework, called hierarchical token grouping, that facilitates vision problem solving by providing a consistent and systematic environment for integrating modules, cues, and knowledge, all in a globally coherent mechanism.< >
This paper addresses the issue of tracking tubular objects, particularly blood vessels from MR images. A model-based approach is adopted. The generalized stochastic tube (GST) model is developed which is an extension ...
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A model-based approach is used for recognizing arterial blood vessels from MRA volumetric data. The modeling includes (1) a generalized stochastic tube model characterizing the structural properties of the vessels, an...
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