All a b c d e f g h i j k l m n o p q r s t u v w x y z Other

Page 1

Displaying 1 – 12 of 12

Showing per page

A blind definition of shape

J. L. Lisani, J. M. Morel, L. Rudin (2002)

ESAIM: Control, Optimisation and Calculus of Variations

In this note, we propose a general definition of shape which is both compatible with the one proposed in phenomenology (gestaltism) and with a computer vision implementation. We reverse the usual order in Computer Vision. We do not define “shape recognition” as a task which requires a “model” pattern which is searched in all images of a certain kind. We give instead a “blind” definition of shapes relying only on invariance and repetition arguments. Given a set of images ℐ , we call shape of this...

A blind definition of shape

J. L. Lisani, J. M. Morel, L. Rudin (2010)

ESAIM: Control, Optimisation and Calculus of Variations

In this note, we propose a general definition of shape which is both compatible with the one proposed in phenomenology (gestaltism) and with a computer vision implementation. We reverse the usual order in Computer Vision. We do not define “shape recognition" as a task which requires a “model" pattern which is searched in all images of a certain kind. We give instead a “blind" definition of shapes relying only on invariance and repetition arguments. Given a set of images ℐ , we call shape of this...

A practical application of kernel-based fuzzy discriminant analysis

Jian-Qiang Gao, Li-Ya Fan, Li Li, Li-Zhong Xu (2013)

International Journal of Applied Mathematics and Computer Science

A novel method for feature extraction and recognition called Kernel Fuzzy Discriminant Analysis (KFDA) is proposed in this paper to deal with recognition problems, e.g., for images. The KFDA method is obtained by combining the advantages of fuzzy methods and a kernel trick. Based on the orthogonal-triangular decomposition of a matrix and Singular Value Decomposition (SVD), two different variants, KFDA/QR and KFDA/SVD, of KFDA are obtained. In the proposed method, the membership degree is incorporated...

A viscosity solution method for Shape-From-Shading without image boundary data

Emmanuel Prados, Fabio Camilli, Olivier Faugeras (2006)

ESAIM: Mathematical Modelling and Numerical Analysis

In this paper we propose a solution of the Lambertian shape-from-shading (SFS) problem by designing a new mathematical framework based on the notion of viscosity solution. The power of our approach is twofolds: (1) it defines a notion of weak solutions (in the viscosity sense) which does not necessarily require boundary data. Moreover, it allows to characterize the viscosity solutions by their “minimums”; and (2) it unifies the works of [Rouy and Tourin, SIAM J. Numer. Anal.29 (1992) 867–884],...

Classification of Images Background Subtraction in Image Segmentation

Francesco Mola, Jaromír Antoch, Luca Frigau, Claudio Conversano (2016)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

Many image segmentation algorithms have been proposed to partition an image into foreground regions of interest and background regions to be ignored. These algorithms use pixel intensities to partition the image, so it should be good practice to choose an appropriate background color as different as possible from the foreground one. In the case of a unique digitizing operation the user can make the choice of background color by himself in order to obtain a good result in the segmentation process,...

Probabilistic mixture-based image modelling

Michal Haindl, Vojtěch Havlíček, Jiří Grim (2011)

Kybernetika

During the last decade we have introduced probabilistic mixture models into image modelling area, which present highly atypical and extremely demanding applications for these models. This difficulty arises from the necessity to model tens thousands correlated data simultaneously and to reliably learn such unusually complex mixture models. Presented paper surveys these novel generative colour image models based on multivariate discrete, Gaussian or Bernoulli mixtures, respectively and demonstrates...

Rotation to physiological factors revised

Miroslav Kárný, Martin Šámal, Josef Böhm (1998)

Kybernetika

Reconstruction of underlying physiological structures from a sequence of images is a long-standing problem which has been solved by factor analysis with a success. This paper tries to return to roots of the problem, to exploit the available findings and to propose an improved paradigm.

Statistical models for deformable templates in image and shape analysis

Stéphanie Allassonnière, Jérémie Bigot, Joan Alexis Glaunès, Florian Maire, Frédéric J.P. Richard (2013)

Annales mathématiques Blaise Pascal

High dimensional data are more and more frequent in many application fields. It becomes particularly important to be able to extract meaningful features from these data sets. Deformable template model is a popular way to achieve this. This paper is a review on the statistical aspects of this model as well as its generalizations. We describe the different mathematical frameworks to handle different data types as well as the deformations. We recall the theoretical convergence properties of the estimators...

Weighted Elastic Net Model for Mass Spectrometry Imaging Processing

D. Hong, F. Zhang (2010)

Mathematical Modelling of Natural Phenomena

In proteomics study, Imaging Mass Spectrometry (IMS) is an emerging and very promising new technique for protein analysis from intact biological tissues. Though it has shown great potential and is very promising for rapid mapping of protein localization and the detection of sizeable differences in protein expression, challenges remain in data processing due to the difficulty of high dimensionality and the fact that the number of input variables in...

Currently displaying 1 – 12 of 12

Page 1