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Journal ArticleDOI

Closed contour extraction application to meteorological pictures

Vincent Lattuati, +1 more
- 01 Jan 1982 - 
- Vol. 15, Iss: 3, pp 145-152
TLDR
Application of the closed contour extraction method to meteorological satellite images proved to be successful while classical methods would have failed.
About
This article is published in Pattern Recognition.The article was published on 1982-01-01. It has received 5 citations till now. The article focuses on the topics: Quantization (image processing).

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Citations
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Journal ArticleDOI

Modeling of Atmospheric Disturbances in Meteorological Pictures

TL;DR: A model-based approach to perform tracking of extratropical atmospheric disturbances from a sequence of satellite cloud-cover images, and the estimation of motion of these spiral-shaped cloud systems and the measurement of the evolution of their shape are described.
Proceedings ArticleDOI

Classification of storms based on their boundaries and cloud top temperatures using satellite imagery

TL;DR: In this article, a system for interpreting and classifying severe weather patterns is presented, which uses several image-processing and pattern-recognition techniques to detect storms in satellite cloud cover imagery.
Journal ArticleDOI

Investigation of Algorithms for Calculating Target Region Area

TL;DR: In order to overcome the shortcomings of common algorithms and obtain a more simple and effective algorithm, the knowledge of mathematical morphology is studied and a new algorithm based on an improved algorithm of contour extracting for calculating target area is proposed.
Journal ArticleDOI

Feature Extraction and Classification of Cell Morphology in Response to the Cell Cycle

TL;DR: A method which recognizes the cyclic morphological changes of the cancer cell by image processing and the recognition rate of 93.9 percent was achieved for the training data, indicating that the cell morphology can be recognized by a computer.
Journal ArticleDOI

Automatic description of microstructures: III. Phase particle classification using shape descriptors

TL;DR: The textural primatives, or phase particles, are subjected to shape analysis and a novel mechanism for within class characterization and the study of the distribution of these shapes may provide a new means of following the effects of mechanical processing.
References
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Journal ArticleDOI

Textural Features for Image Classification

TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Book

Digital Picture Processing

TL;DR: The rapid rate at which the field of digital picture processing has grown in the past five years had necessitated extensive revisions and the introduction of topics not found in the original edition.
Journal ArticleDOI

Texture analysis using gray level run lengths

TL;DR: In this paper, a set of texture features based on gray level run lengths is described, and good classification results are obtained with these features on a sets of samples representing nine terrain types.

Texture analysis using grey level run lengths

TL;DR: A set of texture features based on gray level run lengths is described, and good classification results are obtained with these features on a set of samples representing nine terrain types.

A comparative study of texture measures for terrain classification.

J. S. Weszka, +1 more
TL;DR: Three standard approaches to automatic texture classification make use of features based on the Fourier power spectrum, on second-order gray level statistics, and on first-order statistics of gray level differences, respectively; it was found that the Fouriers generally performed more poorly, while the other feature sets all performned comparably.
Related Papers (5)