ELCVIA : Electronic Letters on Computer Vision and Image Analysis
ELCVIA (ISSN electrónico 1577-5097) es una revista exclusivamente electrónica conocida a nivel internacional sobre investigación y aplicaciones de la visión por computadora y el análisis de imágenes. Su comité editorial está formado por expertos reconocidos internacionalmente. Todos los artículos son revisados por especialistas mediante peer-review y actualmente tiene un porcentaje de aceptación del 25% de los artículos recibidos. Los principales objetivos de la revista son:
  • Ser una revista de referencia a nivel internacional en el campo de la Visión por Computador.
  • Ser una publicación de calidad.
  • Ser un medio de comunicación rápido y dinámico, con una revisión rápida de los artículos.
  • Tener índice de impacto dentro de la base de datos de SCI.
Estadísticas de uso Los más consultados
Últimas adquisiciones:
2020-06-04
08:21
10 p, 1011.0 KB Transition region based approach for skin lesion segmentation / Parida, Priyadarsan (GIET University (Rayagada, India). Department of Electronics and Communication Engineering) ; Rout, Ranjita (GIET University (Rayagada, India). Department of Electronics and Communication Engineering)
Skin melanoma is a skin disease that affects nearly 40% of people globally. Manual detection of the area is a time-consuming process and requires expert knowledge. The application of computer vision techniques can simplify this. [...]
2020 - 10.5565/rev/elcvia.1177
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 19 Núm. 1 (2020) , p. 28-39 (Regular Issue)  
2020-03-18
08:12
13 p, 6.4 MB Robust computer vision system for marbling meat segmentation / Campos, Gabriel Fillipe Centini (Universidade Estadual de Londrina. Department of Computer Science) ; Seixas Jr., José Luis (Eötvös Loránd University (Budapest, Hongria). Department of Data Science and Engineering) ; Barbon, Ana Paula A. C. (Universidade Estadual de Londrina. Department of Zootechnology) ; Felinto, Alan Salvany (Universidade Estadual de Londrina. Department of Computer Science) ; Bridi, Ana Maria (Universidade Estadual de Londrina. Department of Zootechnology) ; Barbon Jr., Sylvio (Universidade Estadual de Londrina. Department of Computer Science)
In this study, we developed a robust automatic computer vision system for marbling meat segmentation. Our approach can segment muscle fat in various marbled meat samples using images acquired with different quality devices in an uncontrolled environment, where there was external ambient light and artificial light; thus, professionals can apply this method without specialized knowledge in terms of sample treatments or equipment, as well as without disruption to normal procedures, thereby obtaining a robust solution. [...]
2020 - 10.5565/rev/elcvia.777
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 19 Núm. 1 (2020) , p. 15-27 (Regular Issue)  
2020-02-26
04:39
14 p, 3.3 MB Robust Object Tracking in Infrared Video via Particle Filters / Comas, Edgardo Antonio (Instituto de Investigaciones Científicas y Técnicas para la Defensa (Buenos Aires, Argentina)) ; Stácul, Adrián (Universidad Tecnológica Nacional (Buenos Aires, Argentina)) ; Delrieux, Claudio (Universidad Nacional de Sur (Bahía Blanca, Argentina). Laboratorio de Ciencias de las Imágenes)
In this paper we investigate the effectiveness of particle filters for object tracking in infrared videos. Once the user identifies the target object to be followed in position and size, its most representative feature points are obtained by means of the SURF algorithm. [...]
2020 - 10.5565/rev/elcvia.1185
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 19 Núm. 1 (2020) , p. 1-14 (Regular Issue)  
2020-01-17
07:08
2 p, 924.4 KB Single Sensor Multi-Spectral Imaging / Soria Poma, Xavier
This dissertation presents the benefits of using a multispectral Single Sensor Camera (SSC) that, simultaneously acquire images in the visible and near-infrared (NIR) bands. The principal benefits while addressing problems related to image bands in the spectral range of 400 to 1100 nanometers, there are cost reductions in the hardware setup because only one SSC is needed instead of two; moreover, the cameras' calibration and images alignment are not required anymore. [...]
2019 - 10.5565/rev/elcvia.1194
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 2 (2019) , p. 11-12 (Special Issue on Recent PhD Thesis Dissemination (2018 - 2019))  
2020-01-17
07:08
2 p, 59.7 KB Understanding Eye Movements : Psychophysics and a Model of Primary Visual Cortex / Berga Garreta, David
Humans move their eyes in order to learn visual representations of the world. These eye movements depend on distinct factors, either by the scene that we perceive or by our own decisions. To select what is relevant to attend is part of our survival mechanisms and the way we build reality, as we constantly react both consciously and unconsciously to all the stimuli that is projected into our eyes. [...]
2019 - 10.5565/rev/elcvia.1193
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 2 (2019) , p. 13-15 (Special Issue on Recent PhD Thesis Dissemination (2018 - 2019))  
2020-01-17
07:08
2 p, 111.5 KB Automatic reactivity characterisation of char particles from pulverised coal combustion using computer vision / Chaves, Deisy
Char morphologies produced during pulverised coal combustion may determine coal reactivity which affects the combustion efficiency and the emissions of CO2 in power plants. Commonly, char samples are characterised manually, but this process is subjective and time-consuming. [...]
2019 - 10.5565/rev/elcvia.1191
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 2 (2019) , p. 16-17 (Special Issue on Recent PhD Thesis Dissemination (2018 - 2019))  
2020-01-17
07:08
4 p, 549.4 KB Fully Convolutional Networks for Text Understanding in Scene Images / Bazazian, Dena
Text understanding in scene images has gained plenty of attention in the computer vision community and it is an important task in many applications as text carries semantically rich information about scene content and context. [...]
2019 - 10.5565/rev/elcvia.1187
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 2 (2019) , p. 6-10 (Special Issue on Recent PhD Thesis Dissemination (2018 - 2019))  
2020-01-17
07:08
4 p, 803.1 KB Design and Development of a Computer Vision Algorithm and Tool for Currency Recognition in Indian Vernacular Languages for Visually Challenged People / Raval, Vishwas (The M S University of Baroda (Vadodara, Índia). Department of Computer Science & Engineering)
God created this universe and all living and non-living entities. Human is one of the best among His creations and in Human beings, eyes are the best gift of God to see His creations. As of now, humans are considered as the only developed creatures among God's creations and have developed themselves from Stone Age to the Computing Era. [...]
2019 - 10.5565/rev/elcvia.1186
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 2 (2019) , p. 4-5 (Special Issue on Recent PhD Thesis Dissemination (2018 - 2019))  
2020-01-17
07:08
4 p, 338.2 KB Development of transition region based methods for image segmentation / Parida, Priyadarsan
In this thesis, some transition region based segmentation approaches have developed to perform image segmentation for grayscale and colour images. In computer vision and image understanding applications, image segmentation is an important pre-processing step. [...]
2019 - 10.5565/rev/elcvia.1176
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 2 (2019) , p. 1-3 (Special Issue on Recent PhD Thesis Dissemination (2018 - 2019))  
2019-07-23
06:05
15 p, 2.9 MB Image decomposition using a second-order variational model and wavelet shrinkage / Tran, Minh-Phuong (Ton Duc Thang university (Vietnam). Faculty of Mathematics and Statistics) ; Nguyen, Thanh Nhan (Ho Chi Minh City University of Education (Vietnam). Department of Mathematics)
The paper is devoted to the new model for image decomposition, that splits an image f into three components u+v+w, where u a piecewise-smooth or the "cartoon" component, v a texture component and w the noise part in variational approach. [...]
2019 - 10.5565/rev/elcvia.1162
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 18 Núm. 1 (2019) , p. 92-107 (Regular Issue)