Search results for "Pattern recognition"
showing 10 items of 2301 documents
RECOGNIZABLE PICTURE LANGUAGES
1992
The purpose of this paper is to propose a new notion of recognizability for picture (two-dimensional) languages extending the characterization of one-dimensional recognizable languages in terms of local languages and alphabetic mappings. We first introduce the family of local picture languages (denoted by LOC) and, in particular, prove the undecidability of the emptiness problem. Then we define the new family of recognizable picture languages (denoted by REC). We study some combinatorial and language theoretic properties of REC such as ambiguity, closure properties or undecidability results. Finally we compare the family REC with the classical families of languages recognized by four-way a…
A genetic algorithm for image segmentation
2002
The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm.
Smart camera design for intensive embedded computing
2005
Computer-assisted vision plays an important role in our society, in various fields such as personal and goods safety, industrial production, telecommunications, robotics, etc. However, technical developments are still rare and slowed down by various factors linked to sensor cost, lack of system flexibility, difficulty of rapidly developing complex and robust applications, and lack of interaction among these systems themselves, or with their environment. This paper describes our proposal for a smart camera with real-time video processing capabilities. A CMOS sensor, processor and, reconfigurable unit associated in the same chip will allow scalability, flexibility, and high performance.
Modeling, simulation and design optimization of a hoisting rig active heave compensation system
2012
Published version of an article in the journal: International Journal of Machine Learning and Cybernetics. Also available from the publisher at: http://dx.doi.org/10.1007/s13042-012-0076-x The objective of this paper is to present an approach in developing a virtual active heave compensation system for a draw-works on a hoisting rig. A virtual system enables quicker overall product development time of a physical system as well as flexibility in optimizing the design parameters. Development of the virtual system started with the modelling of the draw-works and hoisting rig dynamics. Simulations of this model were run in two operational modes while subject to a sinusoidal wave: heave compensa…
TESTING SIMILARITY COEFFICIENTS FOR ANALYSIS OF THE FOSSIL RECORD USING CLUSTERING METHODS: THE PALAEOZOIC FLORA AS A STUDY CASE
2020
This paper reports a global methodological approach based on the similarity and clustering methods of the Palaeozoic plant fossil record using a comparative approach between two similarity measures: the Jacard and Raup-Crick Coefficients. The results show that although the Raup-Crick Coefficients clearly have the potential for providing more robust results, the consequences of the extinction processes are better reflected in the similarity analysis based on the Jaccard Coefficients. On the other hand, the cluster analysis based on UPGMA algorithm shows four robust clusters and reveals new evidence for the singularity of Mississippian flora. Finally, the results obtained reveal that similari…
Comments on “Measurement of dimensionless Chezy coefficient in step-pool reach (Case study of Dizin River in Iran)” by Torabizadeh A., Tahershamsi A.…
2018
This paper is a comment on a previous published paper.
Flow evaluation of red blood cells in capillaroscopic videos
2013
We aim at describing a non-parametric approach to evaluate blood cells velocity in oral capillascopic videos. The proposed methodology is based on the application of standard optical flow algorithms and it is part of a general environment to support during the diagnostic process for evaluating peripheral microcirculation in real time. We validated our approach versus handmade measurements provided by physicians. Results on real data pointed out that our system returns an output coherent to these latter observations.
Texture advection on discontinuous flows
2015
Texture advection techniques, which transport textures using a velocity field, are used to visualize the dynamics of a flow on a triangle mesh. Some flow phenomena lead to velocity fields with discontinuities that cause the deformation of the texture which is not properly controlled by these techniques. We propose a method to detect and visualize discontinuities on a flow, keeping consistent texture advection at both sides of the discontinuity. The method handles the possibility that the discontinuity travels across the domain of the flow with arbitrary velocity, estimating its speed with least-squares approximation. The technique is tested with different sample scenarios and with two avala…
MHT-X: Offline Multiple Hypothesis Tracking with Algorithm X
2021
An efficient and versatile implementation of offline multiple hypothesis tracking with Algorithm X for optimal association search was developed using Python. The code is intended for scientific applications that do not require online processing. Directed graph framework is used and multiple scans with progressively increasing time window width are used for edge construction for maximum likelihood trajectories. The current version of the code was developed for applications in multiphase hydrodynamics, e.g. bubble and particle tracking, and is capable of resolving object motion, merges and splits. Feasible object associations and trajectory graph edge likelihoods are determined using weak mas…
On Unsupervised Methods for Medical Image Segmentation: Investigating Classic Approaches in Breast Cancer DCE-MRI
2021
Unsupervised segmentation techniques, which do not require labeled data for training and can be more easily integrated into the clinical routine, represent a valid solution especially from a clinical feasibility perspective. Indeed, large-scale annotated datasets are not always available, undermining their immediate implementation and use in the clinic. Breast cancer is the most common cause of cancer death in women worldwide. In this study, breast lesion delineation in Dynamic Contrast Enhanced MRI (DCE-MRI) series was addressed by means of four popular unsupervised segmentation approaches: Split-and-Merge combined with Region Growing (SMRG), k-means, Fuzzy C-Means (FCM), and spatial FCM (…