Multi-core based parallel computing technique for content-based image retrieval

• Published in: Journal of Shanghai University Vol. 14; no. 1; pp. 55 - 59
• Main Author: 陈文浩 方昱春 姚继锋 张武
• Format: Journal Article
• Language: English; Chinese
• Published: Heidelberg Shanghai University Press 01.02.2010; School of Computer Engineering and Science,Shanghai University,Shanghai 200072,P.R.China%School of Computer Engineering and Science,Shanghai University,Shanghai 200072,P.R.China; High Performance Computing Center,Shanghai University,Shanghai 200072,P.R.China; Shanghai Supercomputer Center,Shanghai 201203,P.R.China%School of Computer Engineering and Science,Shanghai University,Shanghai 200072,P.R.China
• Subjects: Classical Mechanics; Engineering; Environment; Information Technology; Life Sciences; Materials Science; Mathematical and Computational Engineering; Mechatronics; 医学图像处理; 图像检索系统; 基于内容图像检索; 基于内容的图像检索; 多核心处理器; 并行计算技术; 检索速度; shared-memory; content-based image retrieval (CBIR); feature extraction; parallel computing; similarity comparison
• ISSN: 1007-6417; 1863-236X
• DOI: 10.1007/s11741-010-0111-3

In this paper, we propose a parallel computing technique for content-based image retrieval （CBIR） system. This technique is mainly used for single node with multi-core processor, which is different from those based on cluster or network computing architecture. Due to its specific applications （such as medical image processing） and the harsh terms of hardware resource requirement, the CBIR system has been prevented from being widely used. With the increasing volume of the image database, the widespread use of multi-core processors, and the requirement of the retrieval accuracy and speed, we need to achieve a retrieval strategy which is based on multi-core processor to make the retrieval faster and more convenient than before. Experimental results demonstrate that this parallel architecture can significantly improve the performance of retrieval system. In addition, we also propose an efficient parallel technique with the combinations of the cluster and the multi-core techniques, which is supposed to gear to the new trend of the cloud computing.