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A deep learning-based feature extraction of cloth data using modified grab cut segmentation

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Abstract

In recent years, e-commerce and online shopping have grown tremendously. The development of an image-based cloth retrieval system has become a major research topic in order to effectively and accurately recover required garments from a big database. In this paper, a piecewise feature extraction (PWF) framework is proposed to retrieve the cross-domain clothes. This feature selection strategy is presented to extract optimal features in order to enhance the detection rate while simultaneously simplifying image retrieval computation. First, the user-input query images are collected from online or snapshots. Further clutter backgrounds and different skin textures, of the image, are eliminated via modified GrabCut segmentation. Followed by, the PWF model retrieves the required cloth from the shop domain. In PWF cloth and sleeve size attributes are identified in a separate block with Hough transform and fuzzy rule. Consequently, high-level features are extracted by using a novel RetrieveNet. BAM (Bottleneck attention module) of the RetrieveNet emphasizes the network to focus on the domain features of the input cloth. Finally, the L2 norm is employed to determine the degree of similarity between the shop and query cloths. Based on the similarity, related clothes are retrieved. DARN and Deepfashion2, public datasets are exploited to validate the proposed model, showing that the top-50 image retrieval accuracy is 69.54% and 47.29%, respectively. The efficiency of the proposed clothes retrieval approach is demonstrated by the outcomes of our experiments.

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Acknowledgements

The authors with a deep sense of gratitude would thank the supervisor for his guidance and constant support rendered during this research.

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The authors received no specific funding for this study.

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  1. Department of Computer Science and Engineering, College of Engineering, Anna University, Guindy, Chennai, 600025, India

    M. S. Saranya & P. Geetha

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  1. M. S. Saranya
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Correspondence to M. S. Saranya.

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Saranya, M.S., Geetha, P. A deep learning-based feature extraction of cloth data using modified grab cut segmentation. Vis Comput 39, 4195–4211 (2023). https://doi.org/10.1007/s00371-022-02584-1

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