Research Papers

Integrated visual vocabulary in latent Dirichlet allocation–based scene classification for IKONOS image

[+] Author Affiliations
Retno Kusumaningrum

Diponegoro University, Department of Informatics, Jl. Prof. H. Soedarto SH Tembalang Semarang 50275, Indonesia

Hong Wei

University of Reading, School of Systems Engineering, Reading, RG6 6AY, United Kingdom

Ruli Manurung

University of Indonesia, Faculty of Computer Science, Kampus UI Depok 16424, Indonesia

Aniati Murni

University of Indonesia, Faculty of Computer Science, Kampus UI Depok 16424, Indonesia

J. Appl. Remote Sens. 8(1), 083690 (Jan 20, 2014). doi:10.1117/1.JRS.8.083690
History: Received May 10, 2013; Revised December 11, 2013; Accepted December 16, 2013
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Abstract.  Scene classification based on latent Dirichlet allocation (LDA) is a more general modeling method known as a bag of visual words, in which the construction of a visual vocabulary is a crucial quantization process to ensure success of the classification. A framework is developed using the following new aspects: Gaussian mixture clustering for the quantization process, the use of an integrated visual vocabulary (IVV), which is built as the union of all centroids obtained from the separate quantization process of each class, and the usage of some features, including edge orientation histogram, CIELab color moments, and gray-level co-occurrence matrix (GLCM). The experiments are conducted on IKONOS images with six semantic classes (tree, grassland, residential, commercial/industrial, road, and water). The results show that the use of an IVV increases the overall accuracy (OA) by 11 to 12% and 6% when it is implemented on the selected and all features, respectively. The selected features of CIELab color moments and GLCM provide a better OA than the implementation over CIELab color moment or GLCM as individuals. The latter increases the OA by only 2 to 3%. Moreover, the results show that the OA of LDA outperforms the OA of C4.5 and naive Bayes tree by 20%.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Retno Kusumaningrum ; Hong Wei ; Ruli Manurung and Aniati Murni
"Integrated visual vocabulary in latent Dirichlet allocation–based scene classification for IKONOS image", J. Appl. Remote Sens. 8(1), 083690 (Jan 20, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083690


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