Exploration of preprocessing architectures for field-programmable gate array-based thermal-visual smart camera
2016 (English)In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 25, no 4, article id 041006Article in journal (Refereed) Published
Resource type
Text
Abstract [en]
Embedded smart cameras are gaining in popularity for a number of real-Time outdoor surveillance applications. However, there are still challenges, i.e., computational latency, variation in illumination, and occlusion. To solve these challenges, multimodal systems, integrating multiple imagers can be utilized. However, trade-off is more stringent requirements on processing and communication for embedded platforms. To meet these challenges, we investigated two low-complexity and high-performance preprocessing architectures for a multiple imagers' node on a field-programmable gate array (FPGA). In the proposed architectures, majority of the tasks are performed on the thermal images because of the lower spatial resolution. Analysis with different sets of images show that the system with proposed architectures offers better detection performance and can reduce output data from 1.7 to 99 times as compared with full-size images. The proposed architectures can achieve a frame rate of 53 fps, logics utilization from 2.1% to 4.1%, memory consumption 987 to 148 KB and power consumption in the range of 141 to 163 mW on Artix-7 FPGA. This concludes that the proposed architectures offer reduced design complexity and lower processing and communication requirements while retaining the configurability of the system.
Place, publisher, year, edition, pages
2016. Vol. 25, no 4, article id 041006
Keywords [en]
architecture, field-programmable gate array, preprocessing, smart camera, thermal
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-28491DOI: 10.1117/1.JEI.25.4.041006ISI: 000387787000006Scopus ID: 2-s2.0-84973466871Local ID: STCOAI: oai:DiVA.org:miun-28491DiVA, id: diva2:949673
Note
CODEN: JEIME
2016-07-222016-07-212017-06-30Bibliographically approved