Y. Fujita, F. An, A. Luo, X. Zhang, Lei Chen, H. Mattausch
{"title":"基于像素的流水线硬件架构,用于高性能haar类特征提取","authors":"Y. Fujita, F. An, A. Luo, X. Zhang, Lei Chen, H. Mattausch","doi":"10.1109/APCCAS.2016.7804044","DOIUrl":null,"url":null,"abstract":"Feature extraction, which is one of the basic tasks for pattern recognition, has often high computational cost and large memory usage. In this work, we propose a pixel-based pipeline hardware architecture for Haar-like feature extraction, implemented in 0.18 μm CMOS technology with 1.76 mm2 core area. Pixel-input speed relies on the working frequency of the image sensor so that features are extracted in real time without on-chip image buffer and complex computational procedures. The fabricated chip consumes 4.78 mW power at 1.8 V supply voltage and 12.5 MHz frequency during 30 fps VGA video input. Furthermore, a processing time of 3.07 ms per VGA frame with power dissipation of 36.25 mW at 100 MHz frequency is possible.","PeriodicalId":6495,"journal":{"name":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pixel-based pipeline hardware architecture for high-performance Haar-like feature extraction\",\"authors\":\"Y. Fujita, F. An, A. Luo, X. Zhang, Lei Chen, H. Mattausch\",\"doi\":\"10.1109/APCCAS.2016.7804044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Feature extraction, which is one of the basic tasks for pattern recognition, has often high computational cost and large memory usage. In this work, we propose a pixel-based pipeline hardware architecture for Haar-like feature extraction, implemented in 0.18 μm CMOS technology with 1.76 mm2 core area. Pixel-input speed relies on the working frequency of the image sensor so that features are extracted in real time without on-chip image buffer and complex computational procedures. The fabricated chip consumes 4.78 mW power at 1.8 V supply voltage and 12.5 MHz frequency during 30 fps VGA video input. Furthermore, a processing time of 3.07 ms per VGA frame with power dissipation of 36.25 mW at 100 MHz frequency is possible.\",\"PeriodicalId\":6495,\"journal\":{\"name\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCCAS.2016.7804044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.2016.7804044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pixel-based pipeline hardware architecture for high-performance Haar-like feature extraction
Feature extraction, which is one of the basic tasks for pattern recognition, has often high computational cost and large memory usage. In this work, we propose a pixel-based pipeline hardware architecture for Haar-like feature extraction, implemented in 0.18 μm CMOS technology with 1.76 mm2 core area. Pixel-input speed relies on the working frequency of the image sensor so that features are extracted in real time without on-chip image buffer and complex computational procedures. The fabricated chip consumes 4.78 mW power at 1.8 V supply voltage and 12.5 MHz frequency during 30 fps VGA video input. Furthermore, a processing time of 3.07 ms per VGA frame with power dissipation of 36.25 mW at 100 MHz frequency is possible.