VTechWorks Repository :: Browsing by Author "Haralick, Robert M."

Browsing by Author "Haralick, Robert M."

Now showing 1 - 14 of 14

Advanced spatial information processes: modeling and application
Zhang, Mingchuan (Virginia Polytechnic Institute and State University, 1985)
Making full use of spatial information is an important problem in information-processing and decision making. In this dissertation, two Bayesian decision theoretic frameworks for context classification are developed which make full use of spatial information. The first framework is a new multispectral image context classification technique which is based on a recursive algorithm for optimal estimation of the state of a two-dimensional discrete Markov Random Field (MRF). The implementation of the recursive algorithm is a form of dynamic programming. The second framework is based on a stochastic relaxation algorithm and Markov-Gibbs Random Fields. The relaxation algorithm constitutes an optimization using annealing. We also discuss how to estimate the Markov Random Field Model parameters, which is a key problem in using MRF in image processing and pattern recognition. The estimation of transition probabilities in a 2-D MRF is converted into two 1-D estimation problems. Then a Space-varying estimation method for transition probabilities is discussed.
Analyzing perspective line drawings using hypothesis based reasoning
Mulgaonkar, Prasanna Govind (Virginia Polytechnic Institute and State University, 1984)
One of the important issues in the middle levels of computer vision is how world knowledge should be gradually inserted into the reasoning process. In this dissertation, we develop a technique which uses hypothesis based reasoning to reason about perspective line drawings using only the constraints supplied by the equations of perspective geometry. We show that the problem is NP complete, and that it can be solved using modular inference engines for propagating constraints over the set of world level entities. We also show that theorem proving techniques, with their attendant complexity, are not necessary because the real valued attributes of the world can be computed in closed form based only on the spatial relationships between world entities and measurements from the given image.
Design and Architectural Implications of a Spatial Information System
Vaidya, Prashant D.; Shapiro, Linda G.; Haralick, Robert M.; Minden, Gary J. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1982)
Image analysis, at the higher levels, works with extracted regions and line segments and their properties, not with the original raster data. Thus a spatial information system must be able to store points, lines, and areas as well as their properties and interrelationships. In a previous paper (Shapiro and Haralick [22]), we proposed for this purpose an entity-oriented relational database system. In this paper we describe our first experimental spatial information system, which employs these concepts to store and retrieve watershed data for a portion of the state of Virginia. We describe the logical and physical design of the system and discuss the architectural implications.
Determining intrinsic scene characteristics from images
Pong, Ting-Chuen (Virginia Polytechnic Institute and State University, 1984)
Three fundamental problems in computer vision are addressed in this dissertation. The first deals with the problem of how to extract and assemble a rich symbolic representation of the gray level intensity changes in an image. Results show that the facet model based feature extraction scheme proposed here is superior to the other existing techniques. The second problem addressed deals with the interpretation of the resulting structures as three-dimensional object surfaces. The three different shape modules described in this dissertation are found to be useful in the recovery of intrinsic scene characteristics. Finally, mechanisms for interaction among different sources of information obtained from different shape modules are studied. It is demonstrated that interactions among shape modules can enhance the data acquired by different means.
Edges from image
Lee, Shih Jong (Virginia Polytechnic Institute and State University, 1985)
To simulate the edge perception ability of human eyes and detect scene edges from an image, context information and world constraints must be employed in the edge detection process. To accomplish this, two Bayesian decision theoretic frameworks for context dependent edge detection are developed around the local facet edge detector. The first approach uses all the context in the neighborhood of a pixel. The second approach uses the context of the whole image. The mechanism of the context edge detector then assigns a pixel the most probable edge state which is consistent with its assumed edge context. We also demonstrate how world constraints can aid the edge detection process with a lighting compensation and a curvature constraint scheme. The context information and world constraints can also be used to evaluate the performance of different edge detectors. A general edge coherence measure, a robust edge thinness measure, and a general edge correctness measure are developed. Upon comparing the performance of the edge detectors with the context free second directional derivative zero-crossing edge operator, we find that the context dependent edge detector is superior; the world constrained context free edge detectors can also improve the edge result. Finally, some simple edge detection schemes based on morphologic operations are discussed and evaluated. Although their performances are not as good as the other edge operators described in this dissertation, they are acceptable in the images which have reasonably high signal-to-noise ratio. These morphological edge operations can be realized most efficiently in machine vision systems that have special hardware designed for morphologic operations.
Extraction of Lines And Regions From Grey Tone Line Drawing Images
Watson, Layne T.; Arvind, K.; Ehrich, Roger W.; Haralick, Robert M. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1983)
An algorithm is described for extracting lines from grey level digitizations of industrial drawings. The algorithm is robust, non iterati e, and sequential, and includes procedures for differentiating shaded areas from lines. Examples are given for complex regions of a typical mechanical drawing.
Facet model optic flow and rigid body motion
Lee, Jongsoo (Virginia Polytechnic Institute and State University, 1985)
The dissertation uses the facet model technique to compute the optic flow field directly from a time sequence of image frames. Two techniques, an iterative and a non-iterative one, determine 3D motion parameters and surface structure (relative depth) from the computed optic flow field. Finally we discuss a technique for the image segmentation based on the multi-object motion using both optic flow and its time derivative. The facet model technique computes optic flow locally by solving over-constrained linear equations obtained from a fit over 3D (row, column, and time) neighborhoods in an image sequence. The iterative technique computes motion parameters and surface structure using each to update the other. This technique essentially uses the least square error method on the relationship between optic flow field and rigid body motion. The non-iterative technique computes motion parameters by solving a linear system derived from the relationship between optic flow field and rigid body motion and then computes the relative depth of each pixel using the motion parameters computed. The technique also estimates errors of both the computed motion parameters and the relative depth when the optic flow is perturbed.
Fast geometric algorithms
Noga, Mark T. (Virginia Polytechnic Institute and State University, 1984)
This thesis addresses a number of important problems which fall within the framework of the new discipline of Computational Geometry. The list of topics covered includes sorting and selection, convex hull algorithms, the L₁ hull, determination of the minimum encasing rectangle of a set of points, the Euclidean and L₁ diameter of a set of points, the metric traveling salesman problem, and finding the superrange of starshaped and monotone polygons. The main theme of all our work has been to develop a set of very fast state-of-the-art algorithms which supercede any rivals in terms of speed and ease of implementation. In some cases we have refined existing algorithms; for others we have ·developed new techniques which add to the present database of fast adaptive geometric algorithms. What emerges is a collection of techniques that is successful at merging modern tools developed in analysis of algorithms with those of classical geometry.
Low level and intermediate level vision in aerial images
Zuniga, Oscar A. (Virginia Polytechnic Institute and State University, 1988)
Low-level and intermediate-level computer vision tasks are regarded as transformations from lower to higher-level representations of the image information. An edge-based representation that makes explicit linear features and their spatial relationships is developed. Examples are presented in the scene domain of aerial images of urban scenes containing man-made structures. The techniques used are based on a common structural and statistical model of the image data. This model assumes that the image data is adequately represented locally by a bivariate cubic polynomial plus additive independent Gaussian noise. This model, although simple, is shown to be useful for the design of effective computer vision solving tasks. Four low-level computer vision modules are developed. First, a gradient operator which reduces sharply the gradient direction estimate bias that plagues current operators while also reducing sensitivity to noise. Secondly, a Bayes decision procedure for automatic gradient threshold selection that produces results which are superior to those obtained by the best subjective threshold. Thirdly, the new gradient operator and automatic gradient threshold selection are used in Haralick's directional zero-crossing edge operator resulting in improved performance. Finally, a graytone corner detector with significantly better probability of correct corner assignment than other corner detectors available in the literature. Intermediate-level modules are developed for the construction of a number of intermediate level units from linear features. Among these is a linear segment extraction method that uses both, zero-crossing positional and angular information together with their distributional characteristics to accomplish optimal linear segment fitting. Methods for hypothesizing comers and relations of parallelism and collinearity among pairs of linear segments are developed. These relations are used to build higher-level groupings of linear segments that are likely to correspond to cultural objects.
Matching Three-Dimensional Objects Using a Relational Paradigm
Shapiro, Linda G.; Moriarty, John D.; Haralick, Robert M.; Mulgaonkar, Prasanna G. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1980)
A relational model for describing three-dimensional objects has been designed and implemented as part of a database system. The models which provide rough descriptions to be used at the top level of a hierarchy for describing objects, were designed for initial matching attempts on an unknown object. The descriptions are in terms of the set of simple parts of the objects. Simple parts can be sticks (long, thin parts), plates (flat, wide parts) , and blobs (parts that have three significant dimensions). The relations include an attribute-value table for global properties of the object, the properties of the simple parts, binary connection and support relationships, ternary connection relationships, parallel relationships, perpendicular relationships, and binary constraints. An important use of the system is to characterize the similarity and differences between three-dimensional objects. Toward this end, we have defined a measure of relational similarity between three-dimensional object models and a measure of feature similarity, based only on Euclidean distance between attribute-value tables. In a series of experiments, we compare the results of using the two different similarity measures and conclude that the relational similarity is much more powerful than the feature similarity and should be used when grouping the objects in the database for fast access.
Prosthesis control using a nearest neighbor electromyographic pattern classifier
Dening, David Charles (Virginia Polytechnic Institute and State University, 1982)
A prosthesis control strategy using a nearest neighbor electromyographic pattern classifier was investigated with both a real time microprocessor-based controller and offline computational facilities. Four active electrodes for myoelectric signal amplitude detection were interfaced with a microcomputer for data logging and pattern classification. A nearest neighbor algorithm correctly identified arm motions as belonging to one of six pattern classes from 72 percent to 100 percent of the time. There were five vectors for each class in the look-up table. The nearest neighbor pattern classifier was compared to a minimum error rate Bayes classifier under the assumption that the probability densities were distributed as a multivariate normal distribution. Comparable error rates were obtained with the same data vectors. A condensed nearest neighbor classifier was constructed to determine what minimum number of vectors was necessary in the look-up table. This minimum number of vectors ranged from two to six for the majority of the classes. Larger numbers of vectors were placed in the look-up table for classes that were more difficult to classify.
A Spatial Data Structure
Shapiro, Linda G.; Haralick, Robert M. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1979)
No abstract available.
Spatial Reasoning in Remotely Sensed Data
Wang, Shyuan; Elliott, David B.; Campbell, James B. Jr.; Ehrich, Roger W.; Haralick, Robert M. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1981)
Photointerpreters employ a variety of implicit spatial models to provide interpretations from remotely sensed aerial or satellite imagery. The process of making the implicit models explicit and the subsequent use of explicit models in computer processing is difficult. In this paper one application is illustrated: how ridges and valleys can be automatically interpreted from LANDSAT imagery of a mountainous area and how a relative elevation terrain model can be constructed from this interpretation. It is shown how an illumination model is being used to explain many of the features of a LANDSAT image. Finally, it is shown how to examine valleys for the possible presence of streams or rivers and it is shown how a spatial relational model can be set up to make a final interpretation of the river drainage network.
Structural Descriptions And Inexact Matching
Shapiro, Linda G.; Haralick, Robert M. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1979)
In this paper we formally define the structural description of an object and the concepts of exact and inexact matching of two structural descriptions. We discuss the problems associated with a brute-force backtracking tree search for inexact matching and develop several different algorithms to make the tree search more efficient. We develop the formula for the expected number of nodes in the tree for backtracking alone and vith a forward checking algorithm. Finally we present experimental results verifying the theory and showing that forward checking is the most efficient of the algorithms tested.

Browsing by Author "Haralick, Robert M."

Results Per Page

Sort Options