Mathematical morphology supplies powerful tools for low level image analysis, with applications in robotic vision, visual inspection, medicine, texture analysis and many other areas. Many of the mentioned applications...
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A facial feature classification technique that independently captures both the geometric configuration and the image detail of a particular feature is described. The geometric configuration is first extracted by fitti...
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A facial feature classification technique that independently captures both the geometric configuration and the image detail of a particular feature is described. The geometric configuration is first extracted by fitting a deformable template to the shape of the feature (for example, an eye) in the image. This information is then used to geometrically normalize the image in such a way that the feature in the image attains a standard shape. The normalized image of the facial feature is then classified in terms of a set of principal components previously obtained from a representative set of training images of similar features. This classification stage yields a representation vector which can be used for recognition matching of the feature in terms of image detail alone without the complication of changes in facial expression. Implementation of the system is described and results are given for its application to a set of test faces. These results show that features can be reliably recognized using the representation vectors obtained.< >
A method for determining the relative view orientation of randomly acquired projections of asymmetric objects is described. It extends the projection slice theorem by determining the relative orientation of projection...
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A method for determining the relative view orientation of randomly acquired projections of asymmetric objects is described. It extends the projection slice theorem by determining the relative orientation of projections by the location of lines of intersection among the Fourier transforms of the projections in 3D Fourier space. The complete algorithm is described, and its efficacy is demonstrated using real data.< >
This paper is concerned with the methodologies in statistical imageprocessing.and recognition. Specific areas considered are the following: (1) The decision rules in imagerecognition and their comparative evaluation...
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This paper is concerned with the methodologies in statistical imageprocessing.and recognition. Specific areas considered are the following: (1) The decision rules in imagerecognition and their comparative evaluation under finite sample size condition; (2) Statistical feature extraction techniques for image segmentation with emphasis on the statistical characteristic of textural features; (3) Statistical contextual analysis algorithms for images. Emphasis is placed on the contextual pre processing.postprocessing.techniques to implement the optimum decision rules with context; (4) Statistical image modelling techniques including the nonhomogeneous models and the autoregressive models. The software problems involved in these areas are also examined in details.
An approach which allows an arbitrary structure estimation to be embedded into a recursive estimation process that incrementally improves a structure estimate with every new frame that becomes available is discussed. ...
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An approach which allows an arbitrary structure estimation to be embedded into a recursive estimation process that incrementally improves a structure estimate with every new frame that becomes available is discussed. The approach is based on Bayesian estimation theory and the Kalman filter. The authors demonstrate how it may be applied to such domains as depth from motion and depth from shading.< >
The author attempts to solve the structuring function decomposition problem where the structuring function refers to the gray scale structuring element. A morphologically realizable representation for the structuring ...
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The author attempts to solve the structuring function decomposition problem where the structuring function refers to the gray scale structuring element. A morphologically realizable representation for the structuring function that reduces the structuring function decomposition into a series of binary structuring element decompositions is presented. Recursive algorithms that are pipelinable for efficiently performing gray scale morphological operations are developed on the basis of proposed representation and decomposition. The results are beneficial to real-time image analysis in terms of computer architecture and software development.< >
Straight-line edge segments are often used as key features in building scene models. This paper presents techniques for extracting edge segments from a digital picture. Results of line extraction on a few outdoor scen...
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Straight-line edge segments are often used as key features in building scene models. This paper presents techniques for extracting edge segments from a digital picture. Results of line extraction on a few outdoor scenes are also presented.
pattern matching is a widely used procedure in signal processing.computer vision, image and video processing. Recently, methods using Walsh Hadamard Transform (WHT) and Gray-Code kernels (GCK) are successfully applie...
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pattern matching is a widely used procedure in signal processing.computer vision, image and video processing. Recently, methods using Walsh Hadamard Transform (WHT) and Gray-Code kernels (GCK) are successfully applied for fast transform domain pattern matching. This paper introduces strip sum on the image. The sum of pixels in a rectangle can be computed by one addition using the strip sum. Then we propose to use the orthogonal Haar transform (OHT) for pattern matching. Applied for pattern matching, the algorithm using strip sum requires O(log u) additions per pixel to project input data of size N × N onto u 2-D OHT basis while existing fast algorithms require O(u) additions per pixel to project the same data onto u 2-D WHT or GCK basis. Experimental results show the efficiency of pattern matching using OHT.
Snakes, or active contours, are used extensively in computer vision and imageprocessing.applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to concave ...
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Snakes, or active contours, are used extensively in computer vision and imageprocessing.applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to concave boundaries, however, have limited their utility. This paper develops a new external force for active contours, largely solving both problems. This external force, which we call gradient vector flow (GVF) is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. The resultant field has a large capture range and forces active contours into concave regions. Examples on simulated images and one real image are presented.
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