Fusion of data from fuzzy integral-based active and passive colour stereo vision systems for correspondence identification

Abstract

As shown in our previous work, an approach using the fuzzy-integral [3] can be applied to solving the correspondence problem of active colour stereo vision systems [2]. Evaluating the similarity measure derived in [2] enables the identification of a correct match or otherwise indicates at least several possible matches. To reduce the remaining ambiguity further, the novel approach presented here uses data fusion techniques to make use of additional fuzzy feature-based information gathered by passive colour stereo procedures. Our experimental results, which are discussed in the paper, indicate that this new approach is considerably more effective than the approach using only intensity-based information for determining the similarity of line blocks in colour stereo images. We conclude the paper with a discussion of the potential of the method and directions of possible future research.