@inproceedings{02d2fef5991347eeba7146e6755192e7,
title = "Hausdorff-distance enhanced matching of scale invariant feature transform descriptors in context of image querying",
abstract = "Reliable and effective matching of visual descriptors is a key step for many vision applications, e.g. image retrieval. In this paper, we propose to integrate the Hausdorff distance matching together with our pairing algorithm, in order to obtain a robust while computationally efficient process of matching feature descriptors for image-to-image querying in standards datasets. For this purpose, Scale Invariant Feature Transform (SIFT) descriptors have been matched using our presented algorithm, followed by the computation of our related similarity measure. This approach has shown excellent performance in both retrieval accuracy and speed.",
keywords = "image retrieval, conferences, robustness, feature extraction, pattern recognition, computer vision",
author = "J.I. Olszewska and D. Wilson",
year = "2012",
month = jul,
day = "30",
doi = "10.1109/INES.2012.6249809",
language = "English",
isbn = "9781467326940",
series = "IEEE Conference Proceedings",
publisher = "IEEE",
pages = "91--96",
booktitle = "2012 IEEE 16th International Conference on Intelligent Engineering Systems (INES)",
address = "United States",
}