Abstract
Current implementation of probabilistic relaxation labeling (PRL) is based on stationary compatibility coefficients (SCC's). Such labeling frequently diverges from an achieved minimum labeling error. In this correspondence it is shown that by having nonstationary compatibility coefficients (NSCC's) the PRL stabilizes about the minimum error which is obtained during the early iterations. Also, a noniterative labeling algorithm which uses NSCC and has a performance similar to that of the modified PRL is suggested.
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More From: IEEE Transactions on Pattern Analysis and Machine Intelligence
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