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Author Guang Han ♦ Chunxia Zhao
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2008
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Nearest-Neighbor Classifier ♦ Data analysis ♦ Navigation ♦ Local Binary Patterns ♦ Geometry ♦ Image analysis ♦ Image databases ♦ Layout ♦ Lighting ♦ Cameras ♦ Robustness ♦ Scene Images Classification ♦ Image classification
Abstract Classification of textures in scene images is very difficult due to the high variability of the data within and between images caused by effects such as non-homogeneity of the textures, changes in illumination, shadows, foreshortening and self-occlusion. For these reasons, finding proper features and representative training samples for a classifier is very problematic. Even defining the classes that can be discriminated with texture information is not so straightforward. In this paper, a visualization-based approach for training a texture classifier is presented. A improved multi-channel local binary patterns (LBP) in RGB color space are used as textured color features and a K-NN is employed for visual training and classification, providing very promising results in the classification of outdoor scene images.
Description Author affiliation: Coll. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjingz (Guang Han; Chunxia Zhao)
ISBN 9780769533827
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-11-26
Publisher Place Taiwan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 297.53 kB
Page Count 5
Starting Page 100
Ending Page 104

Source: IEEE Xplore Digital Library