Displaying similar documents to “Use of fuzzy techniques for detection of multiple sclerosis small lesions.”

Fuzzy approach for data association in image tracking.

Julio García, José Manuel Molina, Juan Alberto Besada, Javier I. Portillo (2003)

Mathware and Soft Computing

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A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The tracking system captures a sequence of images, preprocesses them to extract the moving regions (blobs), and associates the blobs...

Localization and fuzzy classification of manufacturing defects in sheets of glass.

Luis Junco Navascués, Luciano Sánchez (1998)

Mathware and Soft Computing

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Artificial Vision Systems are commonly used in industrial applications. The low cost of the equipment facilitates the development of new products. In this paper we describe the use of an artificial vision system in one of the phases of a quality control process related to automotive industries: the windshield manufacturing. We intend to localize and classify the defects that were originated while manufacturing the glass that forms the windshield. We will show that a fuzzy classifier,...

Application of fuzzy techniques to the design of algorithms in computer vision.

Eduard Montseny, Pilar Sobrevilla (1998)

Mathware and Soft Computing

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In this paper a method for the design of algorithms is presented which use fuzzy techniques in order to achieve a better vagueness treatment. A base of rules will be developed in order to design the algorithms. Data fuzzification problem is solved by using probability density functions and probability distribution functions, whereas data analysis is set out associating, to each one of the analysis rules, a fuzzy set which will be obtained by applying an aggregation function which will...

Rule weights in a neuro-fuzzy system with a hierarchical domain partition

Krzysztof Simiński (2010)

International Journal of Applied Mathematics and Computer Science

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The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results showing the advantage of their usage are presented.

An automatic hybrid method for retinal blood vessel extraction

Yong Yang, Shuying Huang, Nini Rao (2008)

International Journal of Applied Mathematics and Computer Science

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The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper presents a novel hybrid automatic approach for the extraction of retinal image vessels. The method consists in the application of mathematical morphology and a fuzzy clustering algorithm followed by a purification procedure. In mathematical morphology, the retinal image is smoothed and strengthened so that the blood vessels are enhanced and the background...

Analyzing the reasoning mechanisms in fuzzy rule based classification systems.

Oscar Cordón, María José del Jesús, Francisco Herrera (1998)

Mathware and Soft Computing

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Fuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method classifies a new example with the consequent of the rule with the greatest degree of association. By using this reasoning method, we do not consider the information provided by the other rules that are also compatible (have also been fired) with this example. In this paper we analyze this problem and propose...

Fuzzy sets in computer vision: an overview.

Pilar Sobrevilla, Eduard Montseny (2003)

Mathware and Soft Computing

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Every computer vision level crawl with uncertainty, what makes its management a significant problem to be considered and solved when trying for automated systems for scene analysis and interpretation. This is why fuzzy set theory and fuzzy logic is making many inroads into the handling of uncertainty in various aspects of image processing and computer vision. The growth within the use of fuzzy set theory in computer vision is keeping pace with the use of more complex algorithms...

Visual anomaly detection via soft computing: a prototype application at NASA.

Jesús A. Domínguez, Steven J. Klinko (2003)

Mathware and Soft Computing

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A visual system prototype that detects anomalies or defects in real time under normal lighting operating conditions was built for NASA at the Kennedy Space Center (KSC). The system prototype is basically a learning machine that integrates the three elements of soft computing, Fuzzy Logic (FL), Artificial Neural Network (ANN), and Genetic Algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs...