ELCVIA : Electronic Letters on Computer Vision and Image Analysis
ELCVIA (ISSN electrònic 1577-5097) és una revista exclusivament electrònica coneguda a nivell internacional sobre recerca i aplicacions de la visió per computador i l’anàlisi d’imatges. El seu comitè editorial està format per experts reconeguts a nivell internacional. Tots els articles són revisats per especialistes mitjançant peer-review, i actualment té un percentatge d'acceptació del 25% dels articles rebuts. Els principals objectius de la revista són:
  • Ser una revista de referència a nivell internacional dins del camp de la Visió per Computador.
  • Ser una publicació de qualitat.
  • Ser un mitjà de comunicació ràpid i dinàmic, amb una revisió ràpida dels articles.
  • Tenir índex d'impacte dins la base de dades de l'SCI.
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Darreres entrades:
2021-08-28
05:24
15 p, 1.2 MB Accuracy improvement of the inSAR quality-guided phase unwrapping based on a modified PDV map / Bentahar, Tarek (Larbi Tebessi University. Laboratory of electrical engineering-telecommunications-LABGET)
In this paper, an accuracy improvement of the quality-guided phase unwrapping algorithm is proposed. Our proposal is based on a modified phase derivative variance which provides more details on local variations especially for important patterns such as fringes and edges, hence distorted regions may be re-unwrapped according to this new reliable PDV. [...]
2021 - 10.5565/rev/elcvia.1220
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 2 (2021) (Regular Issue)  
2021-06-02
06:10
21 p, 1.1 MB Modeling and Analysis of Facial Expressions Using Optical Flow-Derived Divergence and Curl Templates / Anthwal, Shivangi (Indira Gandhi Delhi Technical University for Women)
Facial expressions (FEs) are integral part of non-verbal paralinguistic communication as they provide cues vital for perceiving one's emotional state. Assessment of emotions through FEs is an active research domain in computer vision due to its potential applications in multifaceted domains. [...]
2021 - 10.5565/rev/elcvia.1275
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 2 (2021) , p. 1-21 (Regular Issue)  
2021-05-31
09:48
11 p, 3.5 MB Deep Learning Based Automated Sports Video Summarizationusing YOLO / Guntuboina, Chakradhar (Indus University (Ahmedabad, Índia). Electronics and Communication Engineering Department) ; Porwal, Aditya ; Jain, Preet (Indus University (Ahmedabad, Índia). Electronics and Communication Engineering Department) ; Shingrakhia, Hansa (Indus University (Ahmedabad, Índia). Electronics and Communication Engineering Department)
This paper proposes a computationally inexpensive method for automatic key-event extraction and sub-sequent summarization of sports videos using scoreboard detection. A database consisting of 1300 imageswas used to train (using transfer learning) a supervised-learning based object detection algorithm, YOLO(You Only Look Once). [...]
2021 - 10.5565/rev/elcvia.1286
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 99-116 (Regular Issue)  
2021-05-31
09:48
15 p, 1.2 MB Identification of Suitable Contrast Enhancement Technique for Improving the Quality of Astrocytoma Histopathological Images / Dzulkifli, Fahmi Akmal (University Malaysia Perlis. School of Mechatronic Engineering)
Contrast enhancement plays an important part in image processing. In histology, the application of a contrast enhancement technique is necessary since it can help pathologists in diagnosing the sample slides by increasing the visibility of the morphological and features of cells in an image. [...]
2021 - 10.5565/rev/elcvia.1256
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 84-98 (Regular Issue)  
2021-05-31
09:48
20 p, 756.0 KB Social Video Advertisement Replacement and its Evaluation in Convolutional Neural Networks / Yang, Cheng (Auckland University of Technology (Nova Zelanda). Department of Electrical and Electronic Engineering) ; Yu, Xiang (Auckland University of Technology (Nova Zelanda)) ; Kumar, Arun (National Institute of Technology (Odisha, Índia). Department of Computer Science & Engineering) ; Ali, G.G. Md. Nawaz (University of Charleston (Estats Units d'Amèrica). Department of Applied Computer Science) ; Chong, Peter Han Joo (Auckland University of Technology (Nova Zelanda). Department of Electrical and Electronic Engineering) ; Lam, Patrick (Auckland University of Technology (Nova Zelanda))
This paper introduces a method to use deep convolutional neural networks (CNNs) to automatically replace advertisement (AD) photo on social (or self-media) videos and provides the suitable evaluation method to compare different CNNs. [...]
2021 - 10.5565/rev/elcvia.1347
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 117-136 (Regular Issue)  
2021-03-25
18:51
14 p, 1.1 MB Edge detection algorithm for omnidirectional images, based on superposition laws on Blach's sphere and quantum entropy / Ezzaki, Ayoub (Mohammed V University in Rabat. Physics Department) ; Benkhedra, Dirar (Mohammed V University in Rabat. Mathematic Department) ; El Ansari, Mohamed (My Ismail University in Meknes (Marroc). Computer Science Department) ; Masmoudi, Lhoussaine (Mohammed V University in Rabat. Physics Department)
This paper presents an edge detection algorithm for omnidirectional images based on superposition law onBloch's sphere and quantum local entropy. Omnidirectional vision system has become an essential tool incomputer vision, duo to its large field of view. [...]
2021 - 10.5565/rev/elcvia.1338
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 70-83 (Regular Issue)  
2021-02-25
18:40
15 p, 1.4 MB Recognition of Devanagari Scene Text Using Autoencoder CNN / Shiravale, Sankirti S. (Marathwada Mitra Mandal's College of Engineering (Índia). Department of Computer Engineering) ; Jayadevan, R. (Army Institute of Technology (Pune, Índia). Department of Computer Engineering) ; Sannakki, Sanjeev S. (Gogte Institute of Technology (Belagavi, Índia). Department of Computer Science and Engineering)
Scene text recognition is a well-rooted research domain covering a diverse application area. Recognition of scene text is challenging due to the complex nature of scene images. Various structural characteristics of the script also influence the recognition process. [...]
2021 - 10.5565/rev/elcvia.1344
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 55-69 (Regular Issue)  
2021-01-27
04:57
13 p, 2.0 MB A comparison of an RGB-D camera's performance and a stereocamera in relation to object recognition and spatial position determination / Rodriguez, Julian Severiano (Universidad de San Buenaventura (Bogotá, Colombia))
Results of using an RGB-D camera (Kinect sensor) and a stereo camera, separately, in order to determine the 3D real position of characteristic points of a predetermined object in a scene are presented. [...]
2021 - 10.5565/rev/elcvia.1238
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 16-27 (Regular Issue)  
2021-01-20
04:40
13 p, 3.2 MB Adaptive Window Selection for Non-uniform Lighting Image Thresholding / Pattnaik, Tapaswini (C. V. Raman Global Universityv(Bhubaneswar, Índia). Department of Electronics and Telecommunication Engg) ; Kanungo, Priyadarshi (C. V. Raman Global Universityv(Bhubaneswar, Índia). Department of Electronics and Telecommunication Engg)
Selection of appropriate size of windows or subimages is the most important step for thresholding images with non-uniform lighting. In this paper, a novel criteria function is developed to partition images into different size of sub images appropriate for thresholding. [...]
2021 - 10.5565/rev/elcvia.1301
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 42-54 (Regular Issue)  
2021-01-20
04:40
13 p, 315.6 KB Investigation of Solar Flare Classification to Identify Optimal Performance / Kakde, Aditya (University of Petroleum and Energy Studies) ; Sharma, Durgansh (University of Petroleum and Energy Studies) ; Kaushik, Bhavana (University of Petroleum and Energy Studies) ; Arora, Nitin (Indian Institute of Technology Roorkee)
When an intense brightness for a small amount of time is seen in the sun, then we can say that a solar flare emerged. As solar flares are made up of high energy photons and particles, thus causing the production of high electric fields and currents and therefore results in the disruption in space-borne or ground-based technological system. [...]
2021 - 10.5565/rev/elcvia.1274
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 20 Núm. 1 (2021) , p. 28-41 (Regular Issue)