Edge image description using angular radial
partitioning
A. Chalechale, A. Mertins and G. Naghdy
Abstract: The authors present a novel approach for image representation based on geometric
distribution of edge pixels. Object segmentation is not needed, therefore the input image may
consist of several complex objects. For an efficient description of an arbitrary edge image, the edge
map is divided into M £ N angular radial partitions and local features are extracted for these
partitions. The entire image is then described as a set of spatially distributed invariant feature
descriptors using the magnitude of the Fourier transform. The approach is scale- and rotation-
invariant and tolerates small translations and erosions. The extracted features are characterised by
their compactness and fast extraction/matching time. They exhibit significant improvement in
retrieval performance using the average normalised modified retrieval rank (ANMRR) measure.
Experimental results, using an image database initiated from a movie, confirm the supremacy of the
proposed method.
1
Introduction
Owing to an overwhelming increase in multimedia
information in relevant databases, there is an urgent need
for efficient tools to manage, search and retrieve such
information. Multimedia storage and retrieval has been the
focus of much research in recent years. The field also affects
other disciplines, such as data compression, security and
communication. MPEG-7 and CBIR (content-based image
retrieval) are the two most important multimedia appli-
cations that have addressed this urgent need. MPEG-7 plans
to provide a solution for the problem of efficient (fast) and
effective (correct) retrieval through various multimedia
materials. CBIR aims to facilitate the search in image
databases based on the image content rather than text
retrieval techniques.
In most current content-based image retrieval systems the
emphasis is on four cues: colour, texture, shape and object
layout. MPEG-7 suggests descriptors for colour, texture [1]
and visual shape [2]