{"title":"用于图像识别的word和Simhash的硬件实现","authors":"Shengye Wang, Chen Liang, Xuegong Zhou, Wei Cao, Chen-Mie Wu, Xitian Fan, Lingli Wang","doi":"10.1109/FPT.2013.6718403","DOIUrl":null,"url":null,"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.","PeriodicalId":344469,"journal":{"name":"2013 International Conference on Field-Programmable Technology (FPT)","volume":"293 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A hardware implementation of Bag of Words and Simhash for image recognition\",\"authors\":\"Shengye Wang, Chen Liang, Xuegong Zhou, Wei Cao, Chen-Mie Wu, Xitian Fan, Lingli Wang\",\"doi\":\"10.1109/FPT.2013.6718403\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":344469,\"journal\":{\"name\":\"2013 International Conference on Field-Programmable Technology (FPT)\",\"volume\":\"293 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Field-Programmable Technology (FPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPT.2013.6718403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Field-Programmable Technology (FPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2013.6718403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
诸如Bag of Words和Simhash等算法在图像识别中得到了广泛的应用。为了获得更好的性能和能源效率,本文提出了这两种算法的硬件实现。据我们所知,这是这些算法第一次在硬件上实现图像识别目的。提出的实现能够生成图像的指纹,并在数据库中准确地找到最接近的匹配。它在Xilinx的Virtex-6 SX475T FPGA上实现。通过适当的并行化,可以在高性能和低硬件开销之间取得平衡。实验结果表明,所提出的实现每秒可以处理1,018个图像,大约比英特尔12线程Xeon X5650处理器上的软件快17.8倍。另一方面,与基于软件的实现相比,功耗是0.35倍。因此,在能源效率方面的总体优势高达46倍。所提出的体系结构具有可扩展性,能够满足图像识别的各种需求。
A hardware implementation of Bag of Words and Simhash for image recognition
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.