IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
On naive Bayesian fusion of dependent classifiers
Pattern Recognition Letters
Ultrafast Localization of the Optic Disc Using Dimensionality Reduction of the Search Space
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Automatic detection of the optic disc using majority voting in a collection of optic disc detectors
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Application of majority voting to pattern recognition: an analysis of its behavior and performance
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Generalized weighted majority voting with an application to algorithms having spatial output
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
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In this paper we propose a method for locating the optic disc (OD) in retinal images automatically using a generalization of majority voting scheme. Applying more different optic disc detectors for voting we can achieve better performance for the automatic detection system than for each individual algorithm. The location with maximum number of OD center candidates falling within a radius predefined clinically can be used to localize the OD center. In contrast to the classical voting system we can make good decision if the number of algorithms detecting the optic disc correctly is less than the half of the overall number of algorithms.