计算机工程与应用 ›› 2015, Vol. 51 ›› Issue (14): 23-27.

• 博士论坛 • 上一篇    下一篇

改进的二进制特征图像检索算法

黄  超,刘利强,周卫东   

  1. 哈尔滨工程大学 自动化学院,哈尔滨 150001
  • 出版日期:2015-07-15 发布日期:2015-08-03

Image retrieval based on enhanced binary feature

HUANG Chao, LIU Liqiang, ZHOU Weidong   

  1. College of Automation, Harbin Engineering University, Harbin 150001, China
  • Online:2015-07-15 Published:2015-08-03

摘要: 提出一种针对嵌入式系统的图像检索算法,通过提取目标局部特征来进行图像检索。为了提高检索的实时性并兼顾正确率,选用经典SIFT特征为基础进行改进。在关键点检测阶段使用均值滤波代替高斯滤波大大提高特征提取速度。在描述符生成阶段通过稀疏矩阵将SIFT特征映射为二进制描述符。引入基于K-means的 Multi-probe LSH方法对二进制描述符进行快速检索和匹配。通过一系列的图像缩放、旋转、模糊和光照变化对比实验,可以看出该算法与现有的经典算法相比在检索正确率及实时性方面均有很好的表现。

关键词: 局部特征, 二进制描述符, 尺度不变特征转换(SIFT), 局部敏感哈希(LSH)

Abstract: In this paper it introduces an algorithm of image retrieval for embedded system, which uses local features to do image retrieval. In order to reduce the time cost and get high precision, it improves SIFT feature and descriptor. It replaces Gauss filter with mean filter in detection of scale-space extrema stage. It projects SIFT feature into binary descriptor with sparse matrix. It searches and matches object with multi-probe LSH based on K-means. By doing a series of experiments scale, rotation, blur, illumination, it can draw a conclusion that the algorithm has better performance than traditional state of arts.

Key words: local feature, binary descriptor, Scale-Invariant Feature Transform(SIFT), Locality-Sensitive Hashing(LSH)