Comparing Images Using the Hausdorff Distance
The Hausdorff distance measures the extent to which each point of a model set lies near some point of an image set and vice versa. Thus, this distance can be used to determine the degree of resemblance between two objects that are superimposed on one ...
Optimal Motion and Structure Estimation
The causes of existing linear algorithms exhibiting various high sensitivities to noise are analyzed. It is shown that even a small pixel-level perturbation may override the epipolar information that is essential for the linear algorithms to distinguish ...
Image Description and 3-D Reconstruction From Image Trajectories of Rotational Motion
A new technique for reconstructing the 3-D structure and motion of a scene undergoing relative rotational motion with respect to the camera is discussed. Given image correspondences of point features tracked over many frames, a two-stage technique for ...
Figure-Ground Discrimination: A Combinatorial Optimization Approach
The figure-ground discrimination problem is considered from a combinatorial optimization perspective. A mathematical model encoding the figure-ground discrimination problem that makes explicit a definition of shape based on cocircularity, smoothness, ...
Hybrid Contextural Text Recognition with String Matching
The hybrid contextural algorithm for reading real-life documents printed in varying fonts of any size is presented. Text is recognized progressively in three passes. The first pass is used to generate character hypothesis, the second to generate word ...
Computation of Normalized Edit Distance and Applications
Given two strings X and Y over a finite alphabet, the normalized edit distance between X and Y, d(X,Y) is defined as the minimum of W(P)/L(P), where P is an editing path between X and Y, W(P) is the sum of the weights of the elementary edit operations ...
Segmenting Handwritten Signatures at Their Perceptually Important Points
A new algorithm for segmenting continuous handwritten signatures sampled by a digitizer is described. The segmentation points are found using a two-step procedure. The principal step is to construct a function that weights the perceptual importance of ...
PAC Learning with Generalized Samples and an Applicaiton to Stochastic Geometry
An extension of the standard probably approximately correct (PAC) learning model that allows the use of generalized samples is introduced. A generalized sample is viewed as a pair consisting of a functional on the concept class together with the value ...
Noise-Resistant Invariants of Curves
Projective invariants are shape descriptors that are independent of the point of view from which the shape is seen, and, therefore, are of major importance in object recognition. They make it possible to match an image of an object to one stored in a ...
On Recursive, O(N) Partitioning of a Digitized Curve into Digital Straight Segments
A simple online algorithm for partitioning of a digital curve into digital straight-line segments of maximal length is given. The algorithm requires O(N) time and O(1) space and is therefore optimal. Efficient representations of the digital segments are ...
Fast Nearest-Neighbor Search in Dissimilarity Spaces
A fast nearest-neighbor algorithm is presented. It works in general spaces in which the known cell techniques cannot be implemented for various reasons, such as the absence of coordinate structure or high dimensionality. The central idea has already ...
Learning Bias in Neural Networks and an Approach to Controlling Its Effect in Monotonic Classification
As a learning machine, a neural network using the backpropagation training algorithm is subject to learning bias. This results in unpredictability of boundary generation behavior in pattern recognition applications, especially in the case of small ...
Improved Filtering for the QSIM Algorithm
A source of spurious predictions inside the qualitative simulation algorithm QSIM proposed by B. Kuiper (1986) is identified. The proposed solution involves the use of interval corresponding values for filtering inconsistent states and does not require ...
