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Research on the Style Classification Method of Clothing Commodity Images

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Business Intelligence and Information Technology (BIIT 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 107))

Abstract

E-commerce has a good development trend in commercial digitization. Purchasing clothing products on e-commerce platforms is also the main purchase channel currently selected by consumers. With the development of the times, the public pays more and more attention to the individual pursuit of clothing styles. The current research on the classification of clothing types is relatively complete, but the classification of clothing styles still deserves further research. Based on product style classification, this paper divides 252 suit pictures into two categories: business style and sports style. First, the random walk algorithm segments the foreground of the clothes in the product image from the cluttered background. Then the HOG algorithm is used to extract features from the obtained image data. Finally, the extracted feature vectors are put into the classification model of the support vector machine for binary classification. The result is that the accuracy of style classification after segmentation is better than that without segmentation. It also takes less time to classify after random walk processing.

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Acknowledgments

Fund Project: Philosophy and Social Science Research Planning Project of Heilongjiang Province (20GLE393).

Author information

Authors and Affiliations

  1. Harbin University of Commerce, Harbin, 150028, China

    Yanrong Zhang & Rong Song

  2. Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing, Harbin, 150028, China

    Yanrong Zhang & Rong Song

Authors
  1. Yanrong Zhang
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  2. Rong Song
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Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Yaoqun Xu

  3. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Zhijie Zhao

  4. Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

    Sabah Mohammed

  5. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, Heilongjiang, China

    Zhipeng Fan

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Zhang, Y., Song, R. (2022). Research on the Style Classification Method of Clothing Commodity Images. In: Hassanien, A.E., Xu, Y., Zhao, Z., Mohammed, S., Fan, Z. (eds) Business Intelligence and Information Technology. BIIT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 107. Springer, Cham. https://doi.org/10.1007/978-3-030-92632-8_38

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