Content-based image retrieval for fabric images: A survey

نویسندگان

چکیده

In <span>recent years, a great deal of research has been conducted in the area fabric image retrieval, especially identification and classification visual features. One challenges associated with domain content-based retrieval (CBIR) is semantic gap between low-level features high-level human perceptions. Generally, CBIR includes two main components, namely feature extraction similarity measurement. Therefore, this aims to determine for using techniques grouped into traditional methods convolutional neural networks (CNN). Traditional descriptors features, while CNN addresses high-level, called have advantage shorter computation time reduced system requirements. Meanwhile, descriptors, which handle tailored perceptions, large amounts data require time. general, CNN's fully connected layers are used matching query database images. several studies, extracted layer were retrieval. At end layer, hash codes added reduce </span>search

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ژورنال

عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science

سال: 2021

ISSN: ['2502-4752', '2502-4760']

DOI: https://doi.org/10.11591/ijeecs.v23.i3.pp1861-1872