计算机应用与软件2017，Vol.34Issue(4)：249-254,321,7.DOI:10.3969/j.issn.1000-386x.2017.04.042
一种基于视觉词袋模型的图像检索方法
AN IMAGE RETRIEVAL METHOD BASED ON BAG OF VISUAL WORDS MODEL
金铭 1汪友生 1边航 1王雨婷1
作者信息
- 1. 北京工业大学电子信息与控制工程学院 北京 100124
- 折叠
摘要
Abstract
In order to improve the efficiency of image retrieval, an image retrieval method based on BoVW (Bag of Visual Words) model is proposed.On the one hand, in image local feature extraction algorithm, we use box filter with gradient information to form scale space, to retain more image details information.On the other hand, only the Haar wavelet response in the circular neighborhood of the feature point is calculated in the feature expression, which avoids the repeated calculation of the Haar wavelet response and reduces the dimension while guarantee rotational invariance.At the same time, using improved k-means clustering method to construct a weighted visual dictionary, the k-means initial clustering center is selected based on probabilistic calculation method, which reduces the sensitivity of the traditional k-means clustering to the initial clustering center selection.The experimental results show that the proposed method is more efficient than the traditional method, feature extraction speed is increased by about 48% and the precision is improved by more than 2%.关键词
图像检索/视觉词袋模型/局部特征提取/特征聚类Key words
Image retrieval/Bag of visual words model/Local feature extraction/Feature clustering分类
信息技术与安全科学引用本文复制引用
金铭,汪友生,边航,王雨婷..一种基于视觉词袋模型的图像检索方法[J].计算机应用与软件,2017,34(4):249-254,321,7.
