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2017 | OriginalPaper | Chapter

Similar Trademark Image Retrieval Integrating LBP and Convolutional Neural Network

Authors : Tian Lan, Xiaoyi Feng, Zhaoqiang Xia, Shijie Pan, Jinye Peng

Published in: Image and Graphics

Publisher: Springer International Publishing

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Abstract

Trademarks play a very important role in the field of economics and companies and are usually used to distinguish goods among different producers and operators, represent reputation, quality and reliability of firms. In this paper, we utilize convolutional neural network to extract visual features. Then we present a method to extract Uniform LBP features from feature maps of each convolutional layer features based on the pre-trained CNN model. The experiments indicated that the methods we proposed can enhance the robustness of features and solve the drawback of the comparison approach. It is also shown that the methods we proposed get better results in recall, precision and F-Measure in trademark databases including 7139 trademark images and METU trademark database.

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Metadata
Title
Similar Trademark Image Retrieval Integrating LBP and Convolutional Neural Network
Authors
Tian Lan
Xiaoyi Feng
Zhaoqiang Xia
Shijie Pan
Jinye Peng
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-71598-8_21

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