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2017 | OriginalPaper | Chapter

Image Classification Based on Modified BOW Model

Authors : Gaoming Zhang, Jinfu Yang, Shanshan Zhang, Fei Yang

Published in: Information Technology and Intelligent Transportation Systems

Publisher: Springer International Publishing

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Abstract

Image classifications the basis to solve visual tracking, image segmentation, scenes understanding and other complex visual tasks. Bag of words(Bow) model is initially applied in text classification area, introduced in image proceeding and recognition on account of its simple and effective. This paper follows the standard bag-of-words pipeline, but substitutes original SIFT descriptor with DSP-SIFT(domain-size pooling sift). Then, taking account of the truth that an DSP-SIFT was developed for gray images which limits its performance with regard to some colored objects, we present to add CN(color-name) descriptor to collect the color information to form visual words of image. The experimental results over fifteen scene categories and Caltech 101 datasets indicate that our method can achieve very promising performance.

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Metadata
Title
Image Classification Based on Modified BOW Model
Authors
Gaoming Zhang
Jinfu Yang
Shanshan Zhang
Fei Yang
Copyright Year
2017
Book
Information Technology and Intelligent Transportation Systems

Print ISBN: 978-3-319-38769-7

Electronic ISBN: 978-3-319-38771-0

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-38771-0_33

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