a Record control number WOS:000287219100041

a ISBN 978--1--4244-3429--9

a Original cataloging agency NEU GrandLibrary

a Language code of text/sound track or separate title eng

a Classification number QA76

b Item number .A5 2010

a Personal name Abiyev, Rahib H.,

a Title An efficient fractal measure for image texture recognition.

h Medium Electronic Document

c Statement of responsibility, etc Rahib Hidayat Abiyev, Kemal Ihsan Kılıç.

b Name of publisher, distributor, etc IEEE,

c Date of publication, distribution, etc 2010.

a Summary, etc Fractal measures like fractal dimension (FD), lacunarity, succolarity measure the geometrical complexity of objects and could be used to describe texture information of the images. For this purpose different box counting algorithms were developed to estimate FD. However the existing box-counting methods usually suffer from under counting or over counting, introducing difficulties in obtaining the exact value of the FD. This paper focuses on the box-counting's power in uniquely identifying patterns and presents a new approach which considers the aggregate effects of all the gray levels in the boxes, rather than considering only two gray levels, (min and max) as in the case of traditional differential box-counting method. The proposed method uses new counting measure based on volume percentage of the gray levels inside the boxes. Results from experiments tabulated to depict the improved effect of the proposed method in recognition of the noisy test images from Brodatz Texture and normal test images from CASIA-V3 Iris Databases.

a Topical term or geographic name as entry element Computer science

a Topical term or geographic name as entry element Near East University Article

a Topical term or geographic name as entry element Yakın Doğu Üniversitesi Makale

a Main entry heading 2009 fifth international conference on soft computing, computing with words and perceptions in system analysis, decision and control

g Relationship information 2010 p.161-164.

u Uniform Resource Identifier http://library.neu.edu.tr:2048/login?url=http://dx.doi.org/10.1109/ICSCCW.2009.5379454