Saipullah, Khairul Muzzammil (2011) A Robust Texture Feature Extraction using the Localized Angular Phase. Multimedia Tools and Applications. pp. 717-747. ISSN 1380-7501
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Abstract
This paper proposes a novel descriptor, referred to as the localized angular phase (LAP), which is robust to illumination, scaling, and image blurring. LAP utilizes the phase information from the Fourier transform of the pixels in localized polar space with a fixed radius. The application examples of LAP are presented in terms of content-based image retrieval, classification, and feature extraction of realworld degraded images and computer-aided diagnosis using medical images. The experimental results show that the classification performance of LAP in terms of the latter application examples are better than those of local phase quantization (LPQ), local binary patterns (LBP), and local Fourier histogram (LFH). Specially, the capability of LAP to analyze degraded images and classify abnormal regions in medical images are superior to those of other methods since the best overall classification accuracy of LAP, LPQ, LBP, and LFH using degraded textures are 91.26, 61.23, 35.79, and 33.47%, respectively, while the sensitivity of LAP, LBP, and spatial gray level dependent method (SGLDM) in classifying abnormal lung regions in CT images are 100, 95.5, and 93.75%, respectively.
Item Type: | Article |
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Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Faculty of Electronics and Computer Engineering > Department of Computer Engineering |
Depositing User: | Engr. Khairul Muzzammil Saipullah |
Date Deposited: | 12 Jul 2013 09:18 |
Last Modified: | 28 May 2015 03:57 |
URI: | http://eprints.utem.edu.my/id/eprint/8555 |
Statistic Details: | View Download Statistic |
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