收稿日期: 2016-08-20
修回日期: 2016-10-18
网络出版日期: 2017-03-30
基金资助
国家“863”高技术研究发展计划基金（No.2014AA015202）；国家自然科学基金（No.61272028，No.61572067）；北京市自然基金（No.4162050）；广东省自然科学基金（No.2016A030313708）资助
Euclidean Double Bits Embedding Hashing for Image Retrieval
Received date: 2016-08-20
Revised date: 2016-10-18
Online published: 2017-03-30
李蕾, 岑翼刚, 赵瑞珍, 崔丽鸿, 王艳红 . 基于欧氏距离双比特嵌入哈希的图像检索[J]. 应用科学学报, 2017 , 35(2) : 193 -206 . DOI: 10.3969/j.issn.0255-8297.2017.02.006
We propose a double-bit embedding hashing method based on the Euclidean distance (DBE-E). Euclidean distance is used to measure similarity between the binary hash codes to better preserve similarity relations of the original feature space and improve retrieval precision. To speed computation, bit operation is used to calculate the Euclidean distance between the hash codes. It is 400 times faster than the traditional calculation method of the Euclidean distance for double-bit embedding of 64-bit hash code. Experiments on three image data sets show that the proposed method produces better results than other popular quantization strategies of hashing.
Key words： hashing; double-bit embedding; image retrieval; Euclidean distance
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