DocumentCode :
254557
Title :
A Robust Approach for Singular Point Extraction Based on Complex Polynomial Model
Author :
Jin Qi ; Suxing Liu
Author_Institution :
Electr. Eng. Dept., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2014
fDate :
23-28 June 2014
Firstpage :
78
Lastpage :
83
Abstract :
This paper focuses on a general framework for singular point extraction from vector field. We design a new index of singular point based on complex polynomial model. We test our method in the publicly available benchmark dataset of the singular point detection competition (SPD2010). Our algorithm gets the best results and produces large margins compared to the top five algorithms which took part in the public competition. We also compare our algorithm with the state-of-the-art singular point detection algorithm (called "ZPM" method) with the benchmark. The performance of our method is much better than that of the state-of-the-art method.
Keywords :
feature extraction; object detection; polynomials; vectors; SPD2010 dataset; ZPM method; complex polynomial model; robust approach; singular point detection competition; singular point extraction; vector field; Computational modeling; Convergence; Indexes; Mathematical model; Polynomials; Vectors; Complex Polynomial model; Fingerprint Singular Point; Vector Field;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
Type :
conf
DOI :
10.1109/CVPRW.2014.17
Filename :
6909962
Link To Document :
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