Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9180
Title: A hierarchical algorithm for image multi-labeling
Authors: Hu, J
Lam, KM 
Qiu, GP
Keywords: Label filtering
Multi-label classification
Nearest Neighbors
Issue Date: 2010
Publisher: IEEE
Source: 2010 17th IEEE International Conference on Image Processing (ICIP), 26-29 September 2010, Hong Kong, p. 2349-2352 How to cite?
Abstract: This paper presents an efficient two-stage method for multi-class image labeling. We first propose a simple label-filtering algorithm (LFA), which can remove most of the irrelevant labels for a query image while the potential labels are maintained. With a small population of potential labels left, we then apply the Naive-Bayes Nearest-Neighbor (NBNN) classifier as the second stage of our algorithm to identify the labels for the query image. This approach has been evaluated on the Corel database, and compared to existing algorithms. Experiment results show that our proposed algorithm can achieve a promising result, as it outperforms existing algorithms.
URI: http://hdl.handle.net/10397/9180
ISBN: 978-1-4244-7992-4
978-1-4244-7993-1 (E-ISBN)
ISSN: 1522-4880
DOI: 10.1109/ICIP.2010.5653434
Appears in Collections:Conference Paper

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