Content-based Image Retrieval with Convolutional Neural Networks and Binary Hashing Method

Received: 20-07-2020

Accepted: 02-09-2020

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Issue: Vol. 19 No. 4 (2021)

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KỸ THUẬT VÀ CÔNG NGHỆ

How to Cite:

Huyen, N., Huyen, T., & Luu, V. (2024). Content-based Image Retrieval with Convolutional Neural Networks and Binary Hashing Method. Vietnam Journal of Agricultural Sciences, 19(4), 497–506. http://testtapchi.vnua.edu.vn/index.php/vjasvn/article/view/815

Content-based Image Retrieval with Convolutional Neural Networks and Binary Hashing Method

Nguyen Thi Huyen (*) 1 , Tran Thi Thu Huyen 1 , Vu Thi Luu 1

  • 1 Khoa Công nghệ thông tin, Học viện Nông nghiệp Việt Nam

    • Keywords

    Content-based image retrieval, CBIR, convolutional neural networks, CNN, binary hashing

    Abstract


    Content-based image retrieval has received great attention in recent years because this method overcomes the disadvantages of the text-based image retrieval that is not affected by the lack of or wrong of the text attached to the image. In addition, deep learning methods such as convolutional neural networks have demonstrated their ability to process large-sized data, especially computer vision and image processing. The aims of this study was develop a content-based image retrieval program and method to reduce image query time using the convolutional neural network (CNN). Also, we combined CNN with a binary hashing method to improve image retrieval time. The experimental results on CIFAR-10 and MNIST data sets showed that combining CNN with the binary hashing method for content-based image retrieval achieved an accuracy of approximately 89% on CIFAR-10,98% on MNIST and significantly improved retrieval time.

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