NDLI: A hardware implementation of Bag of Words and Simhash for image recognition

Content Provider	IEEE Xplore Digital Library
Author	Shengye Wang Chen Liang Xuegong Zhou Wei Cao Chenlu Wu Xitian Fan Lingli Wang
Copyright Year	2013
Description	Author affiliation: State Key Lab. of ASIC & Syst., Fudan Univ., Shanghai, China (Shengye Wang; Chen Liang; Xuegong Zhou; Wei Cao; Chenlu Wu; Xitian Fan; Lingli Wang)
Abstract	Algorithms such as Bag of Words and Simhash have been widely used in image recognition. To achieve better performance as well as energy-efficiency, a hardware implementation of these two algorithms is proposed in this paper. To the best of our knowledge, it is the first time that these algorithms have been implemented on hardware for image recognition purpose. The proposed implementation is able to generate a fingerprint of an image and find the closest match in the database accurately. It is implemented on Xilinx's Virtex-6 SX475T FPGA. Tradeoffs between high performance and low hardware overhead are obtained through proper parallelization. The experimental result shows that the proposed implementation can process 1,018 images per second, approximately 17.8x faster than software on Intel's 12-thread Xeon X5650 processor. On the other hand, the power consumption is 0.35x compared to software-based implementation. Thus, the overall advantage in energy-efficiency is as much as 46x. The proposed architecture is scalable, and is able to meet various requirements of image recognition.
Starting Page	418
Ending Page	421
File Size	208726
Page Count	4
File Format	PDF
e-ISBN	9781479921980
DOI	10.1109/FPT.2013.6718403
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-09
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Databases Hardware Field programmable gate arrays Vectors Computer architecture Image recognition FPGA implementation Bag of Words Simhash image recognition
Content Type	Text
Resource Type	Article

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