Accessibility navigation

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

Kusumaningrum, R., Wei, H., Manurung, R. and Murni, A. (2014) Integrated visual vocabulary in latent Dirichlet allocation-based scene classification for IKONOS image. Journal of Applied Remote Sensing, 8 (1). 083690. ISSN 1931-3195

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1117/1.JRS.8.083690


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%. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.JRS.8.083690]

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:36535
Uncontrolled Keywords:latent Dirichlet allocation; scene classification; integrated visual vocabulary; bag of visual words; IKONOS.
Publisher:Society of Photo-optical Instrumentation Engineers (SPIE)

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation