scholarly journals Individuals Identification Based on Palm Vein Matching under a Parallel Environment

2019 ◽  
Vol 9 (14) ◽  
pp. 2805 ◽  
Author(s):  
Ruber Hernández-García ◽  
Ricardo J. Barrientos ◽  
Cristofher Rojas ◽  
Marco Mora
Keyword(s):  
State Of The Art ◽  
Modern Society ◽  
The State ◽  
Time Efficiency ◽  
Matching Process ◽  
Extensive Evaluation ◽  
Parallel Matching ◽  
Vein Recognition ◽  
Palm Vein ◽  
Coarse To Fine

Biometric identification and verification are essential mechanisms in modern society. Palm vein recognition is an emerging biometric technique, which has several advantages, especially in terms of security against forgery. Contactless palm vein systems are more suitable for real-world applications, but two of the major challenges of the state-of-the-art contributions are image deformations and time efficiency. In the present work, we propose a new method for palm vein recognition by combining DAISY descriptor and the Coarse-to-fine PatchMatch (CPM) algorithm in a parallel matching process. Our proposal aims at providing an effective and efficient technique to obtain similarity of palm vein images considering their displacements as discriminatory information. Extensive evaluation on three publicly available databases demonstrates that the discriminability of the proposed approach reaches the state-of-the-art results while it is considerably superior in time efficiency.

scholarly journals Fast Finger Vein Recognition Based on Sparse Matching Algorithm under a Multicore Platform for Real-Time Individuals Identification

Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1167
Author(s):  
Ruber Hernández-García ◽  
Ricardo J. Barrientos ◽  
Cristofher Rojas ◽  
Wladimir E. Soto-Silva ◽  
Marco Mora ◽  
...  
Keyword(s):  
Real Time ◽  
State Of The Art ◽  
Individual Identification ◽  
Affine Transformations ◽  
Private Companies ◽  
Time Efficiency ◽  
Finger Vein ◽  
Vein Recognition ◽  
Coarse To Fine ◽  
Finger Vein Recognition

Nowadays, individual identification is a problem in many private companies, but also in governmental and public order entities. Currently, there are multiple biometric methods, each with different advantages. Finger vein recognition is a modern biometric technique, which has several advantages, especially in terms of security and accuracy. However, image deformations and time efficiency are two of the major limitations of state-of-the-art contributions. In spite of affine transformations produced during the acquisition process, the geometric structure of finger vein images remains invariant. This consideration of the symmetry phenomena presented in finger vein images is exploited in the present work. We combine an image enhancement procedure, the DAISY descriptor, and an optimized Coarse-to-fine PatchMatch (CPM) algorithm under a multicore parallel platform, to develop a fast finger vein recognition method for real-time individuals identification. Our proposal provides an effective and efficient technique to obtain the displacement between finger vein images and considering it as discriminatory information. Experimental results on two well-known databases, PolyU and SDUMLA, show that our proposed approach achieves results comparable to deformation-based techniques of the state-of-the-art, finding statistical differences respect to non-deformation-based approaches. Moreover, our method highly outperforms the baseline method in time efficiency.

scholarly journals Design Challenges for Entity Linking

2015 ◽  
Vol 3 ◽  
pp. 315-328 ◽  
Author(s):  
Xiao Ling ◽  
Sameer Singh ◽  
Daniel S. Weld
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
The State ◽  
Data Sets ◽  
Entity Linking ◽  
Joint Inference ◽  
Extensive Evaluation ◽  
Key Aspects ◽  
Design Challenges

Recent research on entity linking (EL) has introduced a plethora of promising techniques, ranging from deep neural networks to joint inference. But despite numerous papers there is surprisingly little understanding of the state of the art in EL. We attack this confusion by analyzing differences between several versions of the EL problem and presenting a simple yet effective, modular, unsupervised system, called Vinculum, for entity linking. We conduct an extensive evaluation on nine data sets, comparing Vinculum with two state-of-the-art systems, and elucidate key aspects of the system that include mention extraction, candidate generation, entity type prediction, entity coreference, and coherence.

scholarly journals Masculinización de las mujeres en la sociedad moderna: Más allá del equilibrio = Masculinization of women in the modern society: beyond the balance

2019 ◽  
pp. 67
Author(s):  
Gladis Proaño Reyes
Keyword(s):  
Gender Stereotypes ◽  
State Of The Art ◽  
Modern Society ◽  
The State ◽  
Gender Violence ◽  
Per Se ◽  
Las Mujeres

<p class="Normal1"><strong>Resumen</strong></p><p>El presente artículo conjuga el estado del arte de la masculinización de las mujeres y la necesidad de establecer un equilibrio entre el contenido y el alcance de los estereotipos, la violencia de género y muy especialmente, en las fórmulas que los pretenden evitar (a los estereotipos) y erradicar (a la violencia), dado que se parte de la afirmación de que estereotipos de género <em>per se</em> no se traducen en discriminación o desigualdad; es decir, la posible situación de vulnerabilidad que tienen las personas para ser víctimas de violencia de género, no se encuentra intrínsecamente en los roles esperados para ese individuo en la sociedad.</p><p><strong>Abstract</strong></p><p>This article combines the state of the art of masculinization of women and the need to establish a balance between the content and scope of stereotypes, gender violence and, especially, in the formulas that aim to avoid them (to stereotypes) ) and eradicate (violence), since it is based on the assertion that gender stereotypes per se do not translate into discrimination or inequality; that is, the possible situation of vulnerability that people have to be victims of gender violence, is not intrinsically in the roles expected for that individual in society.</p>

scholarly journals Robust Frame Duplication Detection for Degraded Videos

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qi Han ◽  
Hao Chen ◽  
Liyang Yu ◽  
Qiong Li
Keyword(s):  
Image Registration ◽  
State Of The Art ◽  
Locality Sensitive Hashing ◽  
Matching Process ◽  
Correlation Threshold ◽  
Global Optimal ◽  
The Stability ◽  
Duplication Detection ◽  
Coarse To Fine ◽  
Frame Duplication

To detect frame duplication in degraded videos, we proposed a coarse-to-fine approach based on locality-sensitive hashing and image registration. The proposed method consists of a coarse matching stage and a duplication verification step. In the coarse matching stage, visually similar frame sequences are preclustered by locality-sensitive hashing and considered as potential duplication candidates. These candidates are further checked by a duplication verification step. Being different from the existing methods, our duplication verification does not rely on a fixed distance (or correlation) threshold to judge whether two frames are identical. We resorted to image registration, which is intrinsically a global optimal matching process, to determine whether two frames coincide with each other. We integrated the stability information into the registration objective function to make the registration process more robust for degraded videos. To test the performance of the proposed method, we created a dataset, which consists of 3 subsets of different kinds of degradation and 117 forged videos in total. The experimental results show that our method outperforms state-of-the-art methods for most cases in our dataset and exhibits outstanding robustness under different conditions. Thanks to the coarse-to-fine strategy, the running time of the proposed method is also quite competitive.

scholarly journals Fast parallel construction of variable-length Markov chains

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Joel Gustafsson ◽  
Peter Norberg ◽  
Jan R. Qvick-Wester ◽  
Alexander Schliep
Keyword(s):  
Markov Chains ◽  
State Of The Art ◽  
Parallel Implementation ◽  
Probability Distributions ◽  
Information Criterion ◽  
The State ◽  
Variable Length ◽  
Suffix Trees ◽  
Sequence Composition ◽  
Extensive Evaluation

Abstract Background Alignment-free methods are a popular approach for comparing biological sequences, including complete genomes. The methods range from probability distributions of sequence composition to first and higher-order Markov chains, where a k-th order Markov chain over DNA has $$4^k$$ 4 k formal parameters. To circumvent this exponential growth in parameters, variable-length Markov chains (VLMCs) have gained popularity for applications in molecular biology and other areas. VLMCs adapt the depth depending on sequence context and thus curtail excesses in the number of parameters. The scarcity of available fast, or even parallel software tools, prompted the development of a parallel implementation using lazy suffix trees and a hash-based alternative. Results An extensive evaluation was performed on genomes ranging from 12Mbp to 22Gbp. Relevant learning parameters were chosen guided by the Bayesian Information Criterion (BIC) to avoid over-fitting. Our implementation greatly improves upon the state-of-the-art even in serial execution. It exhibits very good parallel scaling with speed-ups for long sequences close to the optimum indicated by Amdahl’s law of 3 for 4 threads and about 6 for 16 threads, respectively. Conclusions Our parallel implementation released as open-source under the GPLv3 license provides a practically useful alternative to the state-of-the-art which allows the construction of VLMCs even for very large genomes significantly faster than previously possible. Additionally, our parameter selection based on BIC gives guidance to end-users comparing genomes.

scholarly journals Systematic review of matching techniques used in model-driven methodologies

2019 ◽  
Vol 19 (3) ◽  
pp. 693-720 ◽  
Author(s):  
Ferenc Attila Somogyi ◽  
Mark Asztalos
Keyword(s):  
State Of The Art ◽  
The State ◽  
Model Matching ◽  
Model Driven ◽  
Textual Representations ◽  
Matching Process ◽  
Software Models ◽  
Open Questions ◽  
Matching Pair ◽  
Matching Techniques

Abstract In model-driven methodologies, model matching is the process of finding a matching pair for every model element between two or more software models. Model matching is an important task as it is often used while differencing and merging models, which are key processes in version control systems. There are a number of different approaches to model matching, with most of them focusing on different goals, i.e., the accuracy of the matching process, or the generality of the algorithm. Moreover, there exist algorithms that use the textual representations of the models during the matching process. We present a systematic literature review that was carried out to obtain the state-of-the-art of model matching techniques. The search process was conducted based on a well-defined methodology. We have identified a total of 3274 non-duplicate studies, out of which 119 have been included as primary studies for this survey. We present the state-of-the-art of model matching, highlighting the differences between different matching techniques, mainly focusing on text-based and graph-based algorithms. Finally, the main open questions, challenges, and possible future directions in the field of model matching are discussed, also including topics like benchmarking, performance and scalability, and conflict handling.

scholarly journals Object Detection in Deep Surveillance

2021 ◽  
Author(s):  
Narina Thakur ◽  
Preeti Nagrath ◽  
Rachna Jain ◽  
Dharmender Saini ◽  
Nitika Sharma ◽  
...  
Keyword(s):  
Object Detection ◽  
State Of The Art ◽  
Pedestrian Detection ◽  
Physical World ◽  
The State ◽  
Person Identification ◽  
Extensive Evaluation ◽  
Aerial Vehicle ◽  
Bounding Boxes ◽  
Surveillance Applications

Abstract Object detection is a key ability required by most computer visions and surveillance applications. Pedestrian detection is a key problem in surveillance, with several applications such as person identification, person count and tracking. The number of techniques to identifying pedestrians in images has gradually increased in recent years, even with the significant advances in the state-of-the-art deep neural network-based framework for object detection models. The research in the field of object detection and image classification has made a stride in the level of accuracy greater than 99% and the level of granularity. A powerful Object detector, specifically designed for high-end surveillance applications, is needed that will not only position the bounding box and label it but will also return their relative positions. The size of these bounding boxes can vary depending on the object and it interacts with the physical world. To address these requirements, an extensive evaluation of the state-of-the-art algorithms has been performed in this paper. The work presented in this paper performs detections on MOT20 dataset using various algorithms and testing on a custom dataset recorded in our organization premises using an Unmanned Aerial Vehicle (UAV). The experimental analysis has been performed on Faster-RCNN, SSD and YOLO models. The Yolov5 model is found to outperform all the other models with 61% precision and 44% of F measure value.

scholarly journals Accurate hierarchical stereo matching based on 3D plane labeling of superpixel for stereo images from rovers

2021 ◽  
Vol 18 (2) ◽  
pp. 172988142110021
Author(s):  
Haichao Li ◽  
Zhi Li ◽  
Jianbin Huang ◽  
Bo Meng ◽  
Zhimin Zhang
Keyword(s):  
Large Scale ◽  
Stereo Matching ◽  
State Of The Art ◽  
The State ◽  
Normal Vector ◽  
Stereo Images ◽  
Disparity Map ◽  
Matching Method ◽  
Search Range ◽  
Coarse To Fine

An accurate hierarchical stereo matching method is proposed based on continuous 3D plane labeling of superpixel for rover’s stereo images. This method can infer the 3D plane label of each pixel combined with the slanted-patch matching strategy and coarse-to-fine constraints, which is especially suitable for large-scale scene matching with low-texture or textureless regions. At every level, the stereo matching method based on superpixel segmentation makes the iteration convergence faster and avoids huge redundant computations. In the coarse-to-fine matching scheme, we propose disparity constraint and 3D normal vector constraint between adjacent levels through which the disparity map and 3D normal vector map at a coarser level are used to restrict the search range of disparity and normal vector at a fine level. The experimental results with the Chang’e-3 rover dataset and the KITTI dataset show that the proposed stereo matching method is efficiently and accurately compared with the state-of-the-art 3D labeling algorithm, especially in low-texture or textureless regions. The computational efficiency of this method is about five to six times faster than the state-of-the-art 3D labeling method, and the accuracy is better.

Practical Picture Processing

1974 ◽  
Vol 32 ◽  
pp. 338-339
Author(s):  
T. A. Welton
Keyword(s):  
Radiation Damage ◽  
Coherence Length ◽  
Spatial Information ◽  
State Of The Art ◽  
Coherent Radiation ◽  
The State ◽  
Energy Spread ◽  
Electron Micrograph ◽  
Picture Processing ◽  
Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

Hypothesis-Evidence Coordination: The State of the Art

2003 ◽  
Vol 48 (6) ◽  
pp. 826-829 ◽  
Author(s):  
Eric Amsel
Keyword(s):  
State Of The Art ◽  
The State
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