362,737 research outputs found
A mutual reference shape based on information theory
International audienceIn this paper, we propose to consider the estimation of a refer-ence shape from a set of different segmentation results using both active contours and information theory. The reference shape is defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations and called a mutual shape. This energy criterion is here justified using similarities between informa-tion theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the speci-ficity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each term of the criterion and interpreted as an evolution equation of an active contour. Some synthetical examples allow us to cast the light on the difference between our mutual shape and an average shape. Our framework has been considered for the estimation of a mutual shape for the evaluation of cardiac segmentation methods in MRI
Ophthalmologic Image Registration Based on Shape-Context: Application to Fundus Autofluorescence (FAF) Images
Online access to subscriber only at http://www.actapress.com/Content_Of_Proceeding.aspx?ProceedingID=494International audienceA novel registration algorithm, which was developed in order to facilitate ophthalmologic image processing, is presented in this paper. It has been evaluated on FAF images, which present low Si gnal/Noise Ratio (SNR) and variations in dynamic grayscale range. These characteristics complicate the registration process and cause a failure to area-based registration techniques [1, 2] . Our method is based on shape-context theory [3] . In the first step, images are enhanced by Gaussian model based histog ram modification. Features are extracted in the next step by morphological operators, which are used to detect an approximation of vascular tree from both reference and floating images. Simplified medial axis of vessels is then calculated. From each image, a set of control points called Bifurcation Points (BPs) is extracted from the medial axis through a new fast algorithm. Radial histogram is formed for each BP using the medial axis. The Chi2 distance is measured between two sets of BPs based on radial histogram. Hungarian algorithm is applied to assign the correspondence among BPs from reference and floating images. The algorithmic robustness is evaluated by mutual information criteria between manual registration considered as Ground Truth and automatic one
A distributed optimization framework for localization and formation control: applications to vision-based measurements
Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures
"Meaning" as a sociological concept: A review of the modeling, mapping, and simulation of the communication of knowledge and meaning
The development of discursive knowledge presumes the communication of meaning
as analytically different from the communication of information. Knowledge can
then be considered as a meaning which makes a difference. Whereas the
communication of information is studied in the information sciences and
scientometrics, the communication of meaning has been central to Luhmann's
attempts to make the theory of autopoiesis relevant for sociology. Analytical
techniques such as semantic maps and the simulation of anticipatory systems
enable us to operationalize the distinctions which Luhmann proposed as relevant
to the elaboration of Husserl's "horizons of meaning" in empirical research:
interactions among communications, the organization of meaning in
instantiations, and the self-organization of interhuman communication in terms
of symbolically generalized media such as truth, love, and power. Horizons of
meaning, however, remain uncertain orders of expectations, and one should
caution against reification from the meta-biological perspective of systems
theory
Bivariate Gamma Distributions for Image Registration and Change Detection
This paper evaluates the potential interest of using bivariate gamma distributions for image registration and change detection. The first part of this paper studies estimators for the parameters of bivariate gamma distributions based on the maximum likelihood principle and the method of moments. The performance of both methods are compared in terms of estimated mean square errors and theoretical asymptotic variances. The mutual information is a classical similarity measure which can be used for image registration or change detection. The second part of the paper studies some properties of the mutual information for bivariate Gamma distributions. Image registration and change detection techniques based on bivariate gamma distributions are finally investigated. Simulation results conducted on synthetic and real data are very encouraging. Bivariate gamma distributions are good candidates allowing us to develop new image registration algorithms and new change detectors
Closed-loop estimation of retinal network sensitivity reveals signature of efficient coding
According to the theory of efficient coding, sensory systems are adapted to
represent natural scenes with high fidelity and at minimal metabolic cost.
Testing this hypothesis for sensory structures performing non-linear
computations on high dimensional stimuli is still an open challenge. Here we
develop a method to characterize the sensitivity of the retinal network to
perturbations of a stimulus. Using closed-loop experiments, we explore
selectively the space of possible perturbations around a given stimulus. We
then show that the response of the retinal population to these small
perturbations can be described by a local linear model. Using this model, we
computed the sensitivity of the neural response to arbitrary temporal
perturbations of the stimulus, and found a peak in the sensitivity as a
function of the frequency of the perturbations. Based on a minimal theory of
sensory processing, we argue that this peak is set to maximize information
transmission. Our approach is relevant to testing the efficient coding
hypothesis locally in any context where no reliable encoding model is known
Configurational Information as Potentially Negative Entropy: The Triple Helix Model
Configurational information is generated when three or more sources of
variance interact. The variations not only disturb each other relationally, but
by selecting upon each other, they are also positioned in a configuration. A
configuration can be stabilized and/or globalized. Different stabilizations can
be considered as second-order variation, and globalization as a second-order
selection. The positive manifestations and the negative selections operate upon
one another by adding and reducing uncertainty, respectively. Reduction of
uncertainty in a configuration can be measured in bits of information. The
variables can also be considered as dimensions of the probabilistic entropy in
the system(s) under study. The configurational information then provides us
with a measure of synergy within a complex system. For example, the knowledge
base of an economy can be considered as such a synergy in the otherwise virtual
(that is, fourth) dimension of a regime
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