Fashion image classification using matching points with linear convolution

Article

Abstract

Social image data related to fashion is flowing through the social networks in huge amount. Analysis of this data is a challenging task due to its characteristics like voluminous, unstructured, etc. Classification provides an easy and efficient way to deal with such data. In this paper, we proposed a new approach for classification of fashion images by incorporating the concepts of linear convolution and matching points using local features. Linear convolution is used to get the representative images with important features. Then, matching points between given image and class representative images are obtained. Maximum matching points are considered while assigning a class label to the given image. Proposed approach is useful further for various applications related to fashion such as fashion recommendation, fashion trend analysis, etc.

Keywords

Linear Convolution Matching Points Classification Fashion images 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.National Institute of Technology GoaPondaIndia

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