State-of-the-art image retrieval pipelines are based on "bag-of-words" matching. We note that the original order in which features are extracted from the image is discarded in the "bag-of-words" matching pipeline. As a result, a set of features extracted from a query image can be transmitted in any order. A set ofm unique features has m! orderings, and if the order of transmission can be discarded, one can reduce the query size by an additional log₂(m!) bits. In this work, we compare two schemes for discarding ordering: one based on Digital Search Trees, and another based on location histograms. We apply the two schemes to a set of low bitrate Compressed Histogram of Gradient (CHoG) features, and compare their performance. Both schemes achieve approximately log₂(m!) reduction in query size for a set of m features.

Date Published: 24 September 2011
PDF: 12 pages
Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 813517 (24 September 2011); doi: 10.1117/12.895431

Published in SPIE Proceedings Vol. 8135:
Applications of Digital Image Processing XXXIV
Andrew G. Tescher, Editor(s)