Displaying similar documents to “Innovative applications of associative morphological memories for image processing and pattern recognition.”

Application of bearing and distance trees to the identification of landmarks on the coast

Tomasz Praczyk (2007)

International Journal of Applied Mathematics and Computer Science

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The problem of continuous position availability is one of the most important issues connected with the human activity at sea. Because the availability of satellite navigational systems can be limited in some cases, e.g. during military operations, one has to consider additional methods of acquiring information about the ship's position. In this paper one of these methods is presented, which is based on exploiting landmarks located on a coastline. A navigational radar is used to obtain...

Fusion based analysis of ophthalmologic image data

Jiří Jan, Radim Kolář, Libor Kubečka, Jan Odstrčilík, Jiří Gazárek (2011)

Kybernetika

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The paper presents an overview of image analysis activities of the Brno DAR group in the medical application area of retinal imaging. Particularly, illumination correction and SNR enhancement by registered averaging as preprocessing steps are briefly described; further mono- and multimodal registration methods developed for specific types of ophthalmological images, and methods for segmentation of optical disc, retinal vessel tree and autofluorescence areas are presented. Finally, the...

Eye localization for face recognition

Paola Campadelli, Raffaella Lanzarotti, Giuseppe Lipori (2006)

RAIRO - Theoretical Informatics and Applications

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We present a novel eye localization method which can be used in face recognition applications. It is based on two SVM classifiers which localize the eyes at different resolution levels exploiting the Haar wavelet representation of the images. We present an extensive analysis of its performance on images of very different public databases, showing very good results.

Comparison of speaker dependent and speaker independent emotion recognition

Jan Rybka, Artur Janicki (2013)

International Journal of Applied Mathematics and Computer Science

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This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector...

Integrated region-based segmentation using color components and texture features with prior shape knowledge

Mehryar Emambakhsh, Hossein Ebrahimnezhad, Mohammad Hossein Sedaaghi (2010)

International Journal of Applied Mathematics and Computer Science

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Segmentation is the art of partitioning an image into different regions where each one has some degree of uniformity in its feature space. A number of methods have been proposed and blind segmentation is one of them. It uses intrinsic image features, such as pixel intensity, color components and texture. However, some virtues, like poor contrast, noise and occlusion, can weaken the procedure. To overcome them, prior knowledge of the object of interest has to be incorporated in a top-down...

Rough sets methods in feature reduction and classification

Roman Świniarski (2001)

International Journal of Applied Mathematics and Computer Science

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The paper presents an application of rough sets and statistical methods to feature reduction and pattern recognition. The presented description of rough sets theory emphasizes the role of rough sets reducts in feature selection and data reduction in pattern recognition. The overview of methods of feature selection emphasizes feature selection criteria, including rough set-based methods. The paper also contains a description of the algorithm for feature selection and reduction based on...