ELCVIA : Electronic Letters on Computer Vision and Image Analysis
ELCVIA (ISSN 1577-5097 E) is an exclusively electronic journal known internationally for research and applications of computer vision and image analysis. Its editorial board consists of internationally renowned experts. All articles are peer reviewed by peer-review and currently has an acceptance rate of 25% of the items received. The main objectives of the magazine are:
    Being a journal of international reference in the field of computer vision. To be a quality publication. Being a media fast and dynamic, with a quick review of the articles. Being Index impact within the SC database.
Latest additions:
2014-06-12
20:24

2 p, 5.0 MB
Semantic Awareness for Automatic Image Interpretation / Lindner, Albrecht ; Qualcomm, San Diego, USA
Finding relations between image semantics and image characteristics is a problem of long standing in computer vision, image analysis or related fields. Classic research in these fields is intended for applications that go from the image domain to the semantic domain such as face recognition or scene understanding. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 11-12
3 documents
2014-06-12
20:15

2 p, 73.4 KB
Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps / Bernal, Jorge ; Universitat Autònoma de Barcelona. Centre de visió per computador
Colorectal cancer is the fourth most common cause of cancer death worldwide and its survival rate depends on the stage in which it is detected on hence the necessity for an early colon screening. There are several screening techniques but colonoscopy is still nowadays the gold standard, although it has some drawbacks such as the miss rate. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 9-10  
2014-06-12
20:05

2 p, 78.0 KB
Optical Flow in Driver Assistance Systems / Onkarappa, Naveen ; Samsung R&D Center, Warsaw, Poland
It is an extended abstract of the PhD thesis titled "Optical Flow in Driver Assistance Systems".
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 61-62  
2014-06-12
19:24

3 p, 32.4 KB
Methods for text segmentation from scene images / Kumar, Deepak ; MILE Laboratory. Department of Electrical Engineering (India)
Camera-captured scene/born-digital image analysis helps in the development of vision for robots to read text, transliterate or translate text, navigate and retrieve search results. However, text in such images does nor follow any standard layout, and its location within the image is random in nature. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 32-34
3 documents
2014-06-12
17:15

2 p, 61.9 KB
Fuzzy Multilevel Graph Embedding for Recognition, Indexing and Retrieval of Graphic Document Images / Muzzamil Luqman, Muhammad
This thesis addresses the problem of lack of efficient computational tools for graph based structural pattern recognition approaches and proposes to exploit computational strength of statistical pattern recognition. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 7-8
3 documents
2014-06-12
16:27

2 p, 71.9 KB
Overcomplete Image Representations for Texture Analysis / Nava, Rodrigo ; Universidad Nacional Autónoma de México
In recent years, computer vision has played an important role in many scientific and technological areas mainlybecause modern society highlights vision over other senses. At the same time, application requirements and complexity have also increased so that in many cases the optimal solution depends on the intrinsic charac-teristics of the problem; therefore, it is difficult to propose a universal image model. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 40-41
2 documents
2014-06-12
16:13

3 p, 770.4 KB
Automatic building detection and land-use classification in urban areas using multispectral high-spatial resolution imagery and LiDAR data / Hermosilla, Txomin ; University of British Columbia. Department of Forest Resources Management
Urban areas areimportant environments, accounting for approximately half the population of theworld. Cities attract residents partly because they offer ample opportunitiesfor development, which often results in urban sprawl and its complex environmentalimplications. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 4-6
2 documents
2014-06-12
15:47

3 p, 2.8 MB
Noise modeling and depth calibration for Time-Of-Flight cameras [Extended Abstract of Ph.D Thesis] / Belhedi, Amira
3D cameras open new perspectives in different application fields such as 3D reconstruction, Augmented Reality and video-surveillance since they provide depth information at high frame-rates. However, they have limitations that affect the accuracy of their measures. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 51-53
2 documents
2014-06-12
15:08

3 p, 119.4 KB
Bioinspired metaheuristics for image segmentation / Osuna-Enciso, Valentín
In general, the purpose of Global Optimization (GO) is finding the global optimum of an objective function defined inside a search space. The GO has applications in many areas of science, engineering, economics, among other, where mathematical models are utilized. [...]
2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 2 (2014) , p. 1-3
3 documents
2014-04-29
14:33

17 p, 592.5 KB
How to separate between Machine-Printed/Handwritten and Arabic/Latin Words ? / Kacem Echi, Afef (University of Tunis) ; Saïdani, Asma (University of Tunis) ; Belaïd, Abdel (University of Lorraine)
This paper gathers some contributions to script and its nature identification. Different sets of features have been employed successfully for discriminating between handwritten and machine-printed Arabic and Latin scripts. [...]
feature contributions. Experiments have been conducted with handwritten and machine-printed words, covering a wide range of fonts. Experimental results show the capability of the proposed features to capture differences between scripts and the effectiveness of the three classifiers. [...]

2014
ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 13, Núm. 1 (2014) , p. 1-16