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Title: SSBC 2018: Sclera segmentation benchmarking competition
Authors: Das, Abhijit
Pal, Umapada
Ferrer, Miguel A. 
Blumenstein, Michael
Stepec, Dejan
Rot, Peter
Emersic, Ziga
Peer, Peter
Struc, Vitomir
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Iris recognition
Image segmentation
Benchmark testing
Task analysis
Cameras, et al
Issue Date: 2018
Journal: International Conference on Biometrics 
Conference: 11th IAPR International Conference on Biometrics, ICB 2018 
Abstract: This paper summarises the results of the Sclera Segmentation Benchmarking Competition (SSBC 2018). It was organised in the context of the 11th IAPR International Conference on Biometrics (ICB 2018). The aim of this competition was to record the developments on sclera segmentation in the cross-sensor environment (sclera trait captured using multiple acquiring sensors). Additionally, the competition also aimed to gain the attention of researchers on this subject of research. For the purpose of benchmarking, we have developed two datasets of sclera images captured using different sensors. The first dataset was collected using a DSLR camera and the second one was collected using a mobile phone camera. The first dataset is the Multi-Angle Sclera Dataset (MASD version 1), which was used in the context of the previous versions of sclera segmentation competitions. The images in the second dataset were captured using .a mobile phone rear camera of 8-megapixel. As baseline manual segmentation mask of the sclera images from both the datasets were developed. Precision and recall-based statistical measures were employed to evaluate the effectiveness of the submitted segmentation technique and to rank them. Six algorithms were submitted towards the segmentation task. This paper analyses the results produced by these algorithms/system and defines a way forward for this subject of research. Both the datasets along with some of the accompanying ground truth/baseline mask will be freely available for research purposes upon request to authors by email.
ISBN: 9781538642856
ISSN: 2376-4201
DOI: 10.1109/ICB2018.2018.00053
Source: 2018 International Conference On Biometrics (Icb) [ISSN 2376-4201], p. 303-308, (2018)
Appears in Collections:Actas de congresos
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