# IEEE Transactions on Pattern Analysis and Machine Intelligence

## Filter Results

Displaying Results 1 - 16 of 16
• ### [Front cover]

Publication Year: 1986, Page(s): c1
| |PDF (755 KB)
• ### List of Contributors

Publication Year: 1986, Page(s): nil1
| |PDF (160 KB)
• ### [Breaker page]

Publication Year: 1986, Page(s): nil1
| |PDF (160 KB)
• ### An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences

Publication Year: 1986, Page(s):565 - 593
Cited by:  Papers (413)  |  Patents (6)
| |PDF (7277 KB)

A mapping between one frame from an image sequence and the preceding or following frame can be represented as a displacement vector field. In most situations, the mere gray value variations do not provide sufficient information in order to estimate such a displacement vector field. Supplementary constraints are necessary, for example the postulate that a displacement vector field varies smoothly a... View full abstract»

• ### A Parallel Algorithm for Stochastic Image Segmentation

Publication Year: 1986, Page(s):594 - 603
Cited by:  Papers (4)
| |PDF (3629 KB)

A parallel algorithm for syntactic image segmentation is introduced. Stochastic tree grammar is used as a context-generating model. It is shown that when this context-generating process is in the equilibrium state, a matched filter can be designed and applied in parallel to the image. This process can be used for image segmentation in a syntactic pattern recognition system to enhance the performan... View full abstract»

• ### An Image Understanding System Using Attributed Symbolic Representation and Inexact Graph-Matching

Publication Year: 1986, Page(s):604 - 618
Cited by:  Papers (80)  |  Patents (3)
| |PDF (5959 KB)

This paper presents a powerful image understanding system that utilizes a semantic-syntactic (or attributed-synibolic) representation scheme in the form of attributed relational graphs (ARG's) for comprehending the global information contents of images. Nodes in the ARG represent the global image features, while the relations between those features are represented by attributed branches between th... View full abstract»

• ### On Optimally Combining Pieces of Information, with Application to Estimating 3-D Complex-Object Position from Range Data

Publication Year: 1986, Page(s):619 - 638
Cited by:  Papers (99)  |  Patents (1)
| |PDF (4680 KB)

New asymptotic methods are introduced that permit computationally simple Bayesian recognition and parameter estimation for many large data sets described by a combination of algebraic, geometric, and probabilistic models. The techniques introduced permit controlled decomposition of a large problem into small problems for separate parallel processing where maximum likelihood estimation or Bayesian ... View full abstract»

• ### A Pyramid-Based Approach to Segmentation Applied to Region Matching

Publication Year: 1986, Page(s):639 - 650
Cited by:  Papers (23)
| |PDF (3223 KB)

In this paper, we attempt to place segmentation schemes utilizing the pyramid architecture on a firm footing. We show that there are some images which cannot be segmented in principle. An efficient segmentation scheme is also developed using pyramid relinking. This scheme will normally have a time complexity which is a sublinear function of the image diameter, which compares favorably to other sch... View full abstract»

• ### Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks

Publication Year: 1986, Page(s):651 - 664
Cited by:  Papers (233)  |  Patents (8)
| |PDF (3647 KB)

We present a system that takes a gray level image as input, locates edges with subpixel accuracy, and links them into lines. Edges are detected by finding zero-crossings in the convolution of the image with Laplacian-of-Gaussian (LoG) masks. The implementation differs markedly from M.I.T.'s as we decompose our masks exactly into a sum of two separable filters instead of the usual approximation by ... View full abstract»

• ### Filtering Closed Curves

Publication Year: 1986, Page(s):665 - 668
Cited by:  Papers (33)  |  Patents (1)
| |PDF (770 KB)

A closed curve in the plane can be described in several ways. We show that a simple representation in terms of radius of curvature versus normal direction has certain advantages. In particular, convolutional filtering of the extended circular image leads to a closed curve. Similar filtering operations applied to some other representations of the curve do not guarantee that the result corresponds t... View full abstract»

• ### Contribution to the Prediction of Performances of the Hough Transform

Publication Year: 1986, Page(s):669 - 674
Cited by:  Papers (43)
| |PDF (2920 KB)

Exact predictions of the performances of the Hough detection of straight lines in two-dimensional images are presented for rectangular and circular retinas, in Cartesian and normal parameterization, in the case of noisy signals. Detection of circles, under the same assumptions, is discussed. The limits of adaptive quantization to reduce intrinsic noise are presented, and it is shown that a signal ... View full abstract»

• ### Comments on Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes''

Publication Year: 1986, Page(s):674 - 675
Cited by:  Papers (1)
| |PDF (1201 KB)
• ### Authors' reply

Publication Year: 1986, Page(s): 675
| |PDF (277 KB)
• ### Comments on Low Level Segmentation: An Expert System''

Publication Year: 1986, Page(s):675 - 676
Cited by:  Papers (2)
| |PDF (472 KB)
• ### Authors' reply

Publication Year: 1986, Page(s): 676
| |PDF (216 KB)
• ### Correction to "Best Linear Unbiased Estimators for Properties of Digitized Straight Lines''

Publication Year: 1986, Page(s): 676
| |PDF (207 KB)

## Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Sven Dickinson
University of Toronto
e-mail: sven@cs.toronto.edu