Abstract
Feeding a noisy signal to a biometric system degrades its performance. Hence, signal quality measure is used to avoid passing irregular signals to subsequent systems such as bio-metric systems. To tackle this issue, 1DMRLBP features, which are 1 dimensional signal feature extraction (inspired by the 2 dimensional image Local Binary Patterns) is proposed. 1DMRLBP with its multi-resolution capability captures local and global signal characteristics; and with its histogram extraction avoids segments misalignment and reduces the number of features. Also with some modifications, 1DMRLBP accommodates the problem of unknown amplitude of a signal. 1DMRLBP achieves 91% performance rate in distinguishing between regular and irregular ECG waveforms. MATLAB code and more information are available at www.comm.utoronto.ca/~wlouis/1DMRLBP.
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