Open AccessEfficient Use of MPEG‐7 Edge Histogram Descriptor
Author(s) -
Won Chee Sun,
Park Dong Kwon,
Park SooJun
Publication year - 2002
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.02.0102.0103
Subject(s) - histogram , histogram matching , artificial intelligence , computer vision , pattern recognition (psychology) , image histogram , matching (statistics) , similarity (geometry) , enhanced data rates for gsm evolution , computer science , mathematics , image (mathematics) , image processing , image texture , statistics
MPEG‐7 Visual Standard specifies a set of descriptors that can be used to measure similarity in images or video. Among them, the Edge Histogram Descriptor describes edge distribution with a histogram based on local edge distribution in an image. Since the Edge Histogram Descriptor recommended for the MPEG‐7 standard represents only local edge distribution in the image, the matching performance for image retrieval may not be satisfactory. This paper proposes the use of global and semi‐local edge histograms generated directly from the local histogram bins to increase the matching performance. Then, the global, semiglobal, and local histograms of images are combined to measure the image similarity and are compared with the MPEG‐7 descriptor of the local‐only histogram. Since we exploit the absolute location of the edge in the image as well as its global composition, the proposed matching method can retrieve semantically similar images. Experiments on MPEG‐7 test images show that the proposed method yields better retrieval performance by an amount of 0.04 in ANMRR, which shows a significant difference in visual inspection.