Integer summing algorithms on reconfigurable meshes
Theoretical Computer Science
Geometric pattern matching: a performance study
SCG '99 Proceedings of the fifteenth annual symposium on Computational geometry
Bounds to Complexities of Networks for Sorting and for Switching
Journal of the ACM (JACM)
A 800 Mpixel/sec reconfigurable image correlator on XC6216
FPL '97 Proceedings of the 7th International Workshop on Field-Programmable Logic and Applications
Content-based image retrieval: approaches and trends of the new age
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Journal on Image and Video Processing - Color in Image and Video Processing
Design and implementation of a fuzzy-modified ant colony hardware structure for image retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
ARC'07 Proceedings of the 3rd international conference on Reconfigurable computing: architectures, tools and applications
Acceleration of a content-based image-retrieval application on the RDISK cluster
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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The main contribution of this paper is to present an image retrieval system using FPGAs. Given a template image T and a database of a number of Images I1, I2,..., our system lists all images that contain a subimage similar to T. More specifically, a hardware generator in our system creates the Verilog HDL source of a hardware that determines whether Ii has a similar subimage to T for any image Ii and a particular template T. The created Verilog HDL source is embed in an FPGA using the design tool provided by the FPGA vendor. Since the hardware embedded in the FPGA is designed for a particular template T, it is an instance-specific hardware that allows us to achieve extreme acceleration. We evaluate the performance of our image matching hardware using a PCI-connected Xilinx FPGA and a timing analyzer. Since the generated hardware attains up to 3000 speed-up factor over the software solution, our approach is promising.