计算机工程与应用2019，Vol.55Issue(23)：194-199,6.DOI:10.3778/j.issn.1002-8331.1809-0039
基于哈希编码和卷积神经网络的图像检索方法
Image Retrieval Based on Hash Coding and Convolutional Neural Network
王妙 1景军锋1
作者信息
- 1. 西安工程大学 电子信息学院,西安 710600
- 折叠
摘要
Abstract
Aiming at the retrieval of images, a method based on Hash coding and Convolutional Neural Network(CNN) is proposed. The idea is to add a Hash layer to the CNN, and a coarse-to-fine search strategy is used to retrieval similar images. Firstly, the coarse-level search is operated according to the Hash coding to obtain the same or similar images to form a pool of m images. Then the Euclidean distances between the high-level semantic features of the m images and query image are calculated for fine-level search, thus achieving the ultimate retrieval purpose. The proposed method takes the loss of Hash layer as one of the optimization goals, and two features are combined for image retrieval, which makes up the shortcomings of time consuming and memory using of the existing methods. The results show that the proposed method outperforms the state-of-art algorithms on printed fabric and CIFAR-10 datasets.关键词
图像检索/卷积神经网络/哈希编码/分级检索Key words
image retrieval/Convolutional Neural Network(CNN)/Hash coding/hierarchical search分类
信息技术与安全科学引用本文复制引用
王妙,景军锋..基于哈希编码和卷积神经网络的图像检索方法[J].计算机工程与应用,2019,55(23):194-199,6.
