A similarity measure for stereo feature matching

An approach to stereo feature matching is presented with the introduction of a similarity measure for evaluating and confirming a stereo match. The contributions of this study are reflected in (1) the development of a similarity measure which evaluates a stereo match based on feature locality and gray-level gradient associated with the feature; and (2) the use of a matching procedure that integrates local and global matching strategies based on matching first those features with the highest similarity measure among the set of all highest similarities found locally under confined search spaces, ensuring that each feature is matched with a high degree of certainty. A left-to-right and right-to-left consistency check is used for each feature to comply with the uniqueness constraint and to confirm if a potential match can be declared a correct match.

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