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Advances in Multimedia
Volume 2015 (2015), Article ID 360186, 10 pages
Research Article

Compact Local Directional Texture Pattern for Local Image Description

1School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
2Vocational & Technical Institute, Hebei Normal University, Shijiazhuang 050024, China

Received 7 May 2015; Revised 5 August 2015; Accepted 18 August 2015

Academic Editor: Chong Wah Ngo

Copyright © 2015 Hui Zeng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents an effective local image feature region descriptor, called CLDTP descriptor (Compact Local Directional Texture Pattern), and its application in image matching and object recognition. The CLDTP descriptor encodes the directional and contrast information in a local region, so it contains the gradient orientation information and the gradient magnitude information. As the dimension of the CLDTP histogram is much lower than the dimension of the LDTP histogram, the CLDTP descriptor has higher computational efficiency and it is suitable for image matching. Extensive experiments have validated the effectiveness of the designed CLDTP descriptor.