Feature Selection in Colour Images for Token Matching
Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Perception. Pages 749-750.
Abstract
We are currently developing an algorithm for knowledge-based correspondence analysis in dynamic stereo images. In this paper we describe the feature selection algorithms and the relational data structure used for matching. We also present a clustering algorithm that is used to group the tokens into sets of similar tokens. The matching algorithm uses this classification information to plan a matching strategy. The least ambiguous image features are matched first and are used as a 'handle' for constraint propagation. We present two algorithms for feature selection in colour images - a region grower and an interest operator, as well as experimental results for point classification and region classification.
@inproceedings{ijcai1987p151,
title = {Feature Selection in Colour Images for Token Matching},
author = {Dreschler-Fischer, Leonie S. and Gnutzmann, Frank},
booktitle = {Proceedings of the Tenth International Joint Conference on
Artificial Intelligence, {IJCAI-87}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John McDermott},
pages = {749--750},
year = {1987},
note = {Perception},
url = {https://ijcai.org/proceedings/1987/151},
}
TY - CPAPER TI - Feature Selection in Colour Images for Token Matching AU - Dreschler-Fischer, Leonie S. AU - Gnutzmann, Frank T2 - Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87 PB - International Joint Conferences on Artificial Intelligence PY - 1987 SP - 749 EP - 750 UR - https://ijcai.org/proceedings/1987/151 ER -Copied
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