Search results for " Segmentation"

Performance evaluation of simple fingerprint minutiae extraction algorithm using crossing number on valley structure

2008

In fingerprint recognition system, performance of fingerprint feature extraction algorithm is important. We use visual analysis to evaluate this performance. 100 respondents fill a questionnaire consisting of 30 images from fingerprint feature extraction process. We get 12,3 % minutiae points missed by this algorithm. With BOZORTH3 minutiae matching algorithm, the distribution of matching score of 80-fingerprint images are presented and we obtain EER 5.89 % at threshold value 180.

An edge-driven 3D region growing approach for upper airways morphology and volume evaluation in patients with Pierre Robin sequence

2016

In this paper, a semi-automatic approach for segmentation of the upper airways is proposed. The implemented approach uses an edge-driven 3D region-growing algorithm to segment ROIs and 3D volume-rendering technique to reconstruct the 3D model of the upper airways. This method can be used to integrate information inside a medical decision support system, making it possible to enhance medical evaluation. The effectiveness of the proposed segmentation approach was evaluated using Jaccard (92.1733%) and dice (94.6441%) similarity indices and specificity (96.8895%) and sensitivity (97.6682%) rates. The proposed method achieved an average computation time reduced by a 16x factor with respect to m…

A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics

2006

We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.

Fuzzy C-Means Segmentation on Brain MR Slices Corrupted by RF-Inhomogeneity

2007

Brain MR Images corrupted by RF-Inhomogeneity exhibit brightness variations in such a way that a standard Fuzzy C-Means (fcm) segmentation algorithm fails. As a consequence, modified versions of the algorithm can be found in literature, which take into account the artifact. In this work we show that the application of a suitable pre-processing algorithm, already presented by the authors, followed by a standard fcm segmentation achieves good results also. The experimental results ones are compared with those obtained using SPM5, which can be considered the state of the art algorithm oriented to brain segmentation and bias removal.

Color and Flow Based Superpixels for 3D Geometry Respecting Meshing

2014

We present an adaptive weight based superpixel segmentation method for the goal of creating mesh representation that respects the 3D scene structure. We propose a new fusion framework which employs both dense optical flow and color images to compute the probability of boundaries. The main contribution of this work is that we introduce a new color and optical flow pixel-wise weighting model that takes into account the non-linear error distribution of the depth estimation from optical flow. Experiments show that our method is better than the other state-of-art methods in terms of smaller error in the final produced mesh.

A Two Stage Neural Architecture for Segmentation and Superquadrics Recovery from Range Data

2002

A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neural networks: a SOM is used to perform data segmentation, and, for each segment, a multilayer feed-forward network performs model estimation.

Assessing preferences of some predefined consumer profiles for attributes of small fruit

2015

Small fruit (commonly referred to as berries), represents a potential high-value niche-market crop in Italy. This fruit grows naturally in many localities of northern Italy, but favorable environmental conditions for this crop can be found also in southern regions where this production may support local farmers' incomes. According to literature and to official statistics, small fruit's health benefiting properties are well known in the international market, but little is known about the reason of a low commercialization rate of fresh small fruit in Italy. The objective of this study was to assess, in the domestic market, consumer preferences for small fruit according to consumer rankings ap…

Automatic Quality Assessment of Cardiac MR Images with Motion Artefacts using Multi-task Learning and K-Space Motion Artefact Augmentation

2022

The movement of patients and respiratory motion during MRI acquisition produce image artefacts that reduce the image quality and its diagnostic value. Quality assessment of the images is essential to minimize segmentation errors and avoid wrong clinical decisions in the downstream tasks. In this paper, we propose automatic multi-task learning (MTL) based classification model to detect cardiac MR images with different levels of motion artefact. We also develop an automatic segmentation model that leverages k-space based motion artefact augmentation (MAA) and a novel compound loss that utilizes Dice loss with a polynomial version of cross-entropy loss (PolyLoss) to robustly segment cardiac st…

The Analysis of Consumer Behavior in Relationship to a Global Brand in the Lodging Industry, Across Europe and North America Abstract: The world is c…

2011

Gestión empresarial y dinámica laboral en España

2015

El objetivo del presente artículo es plantear una serie de reflexiones sobre la dinámica labo- ral reciente en la economía española bajo el enfoque analítico de la segmentación laboral. Desde esta perspectiva, la situación y problemas del mercado laboral se explican por un conjunto de factores relacionados con las prácticas de gestión empresarial y no tanto por la regulación que limita la competencia en el mercado o las modalidades contractuales. Nues- tra conclusión es que es necesario superar el marco analítico restringido del enfoque econó- mico convencional e introducir otras dimensiones, que van más allá del mercado, para una mejor compresión de los problemas laborales. En este sentido…