Photo retrieval based on spatial layout with hardware acceleration for mobile devices
Journal
IEEE Transactions on Mobile Computing
Journal Volume
10
Journal Issue
11
Pages
1646-1660
Date Issued
2011
Author(s)
Abstract
A new photo retrieval system for mobile devices is proposed. The system can be used to search for photos with similar spatial layouts efficiently, and it adopts an image segmentation algorithm that extracts features of image regions based on K-Means clustering. Since K-Means is computationally intensive for real-time applications and prone to generate clustering results with local optima, parallel hardware architectures are designed to meet the real-time requirement of the retrieval process. Experiments show that the proposed algorithm in the photo retrieval system obtains better mean average precision than other methods, and it is tested with image recognition problems. The robustness of the algorithm is also evaluated with noise and image blurring. Besides, the proposed K-Means hardware can provide a trade-off between the execution time and the retrieval performance on the software and hardware cosimulation platform. The contribution of this work is twofold. The first is the development of a photo retrieval framework for mobile devices, where a new texture feature is employed in the algorithm to enhance the retrieval performance. The other is the integration of the K-Means hardware accelerator and the photo retrieval system. The hardware architecture is analyzed, and the specifications are compared with previous works. © 2011 IEEE.
Subjects
hardware acceleration; image segmentation; K-Means clustering; parallel processing; Photo retrieval
Other Subjects
Clustering results; Cosimulation; Execution time; Hardware acceleration; Hardware accelerators; Hardware architecture; Image blurring; Image regions; Image segmentation algorithm; K-means; K-means clustering; Local optima; Parallel hardware; Parallel processing; Photo retrieval; Real time requirement; Real-time application; Retrieval performance; Retrieval process; Spatial layout; Texture features; Clustering algorithms; Hardware; Image recognition; Image segmentation; Information retrieval; Mobile devices; Search engines
Type
journal article