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Image classification based on scheme of principal node analysis

[+] Author Affiliations
Feng Yang

University of Electronic Science and Technology of China, School of Communication and Information Engineering, No. 2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu 611731, China

Wenzhou Medical University, School of Information and Engineering, Chashan Higher Education Park, Wenzhou 325035, China

Zheng Ma

University of Electronic Science and Technology of China, School of Communication and Information Engineering, No. 2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu 611731, China

Mei Xie

University of Electronic Science and Technology of China, School of Electronic Engineering, No. 2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu 611731, China

J. Electron. Imaging. 25(6), 063018 (Dec 13, 2016). doi:10.1117/1.JEI.25.6.063018
History: Received July 24, 2016; Accepted November 16, 2016
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Abstract.  This paper presents a scheme of principal node analysis (PNA) with the aim to improve the representativeness of the learned codebook so as to enhance the classification rate of scene image. Original images are normalized into gray ones and the scale-invariant feature transform (SIFT) descriptors are extracted from each image in the preprocessing stage. Then, the PNA-based scheme is applied to the SIFT descriptors with iteration and selection algorithms. The principal nodes of each image are selected through spatial analysis of the SIFT descriptors with Manhattan distance (L1 norm) and Euclidean distance (L2 norm) in order to increase the representativeness of the codebook. With the purpose of evaluating the performance of our scheme, the feature vector of the image is calculated by two baseline methods after the codebook is constructed. The L1-PNA- and L2-PNA-based baseline methods are tested and compared with different scales of codebooks over three public scene image databases. The experimental results show the effectiveness of the proposed scheme of PNA with a higher categorization rate.

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Citation

Feng Yang ; Zheng Ma and Mei Xie
"Image classification based on scheme of principal node analysis", J. Electron. Imaging. 25(6), 063018 (Dec 13, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.6.063018


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