Architecture of wireless Visual Sensor Node with Region of Interest coding

Imran, Muhammad; Khursheed, Khursheed; Ahmad, Naeem; O’Nils, Mattias; Lawal, Najeem; Waheed, Malik Abdul

doi:10.1109/nesea.2012.6474029

Cited by 7 publications

(9 citation statements)

References 13 publications

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“…8,10 Employing embedded smart cameras for realtime applications puts further constraints on latency and robust surveillance. 8,10 Employing embedded smart cameras for realtime applications puts further constraints on latency and robust surveillance.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…8 However, implementation complexity on the register transfer level (RTL) for FPGA is greater. 8 However, implementation complexity on the register transfer level (RTL) for FPGA is greater.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…8,10,14 In this paragraph, we present a sample of work from published literature in the area of embedded smart camera and multispectral image processing. The increasing demand for on-board computations has motivated the usage of FPGA-based architectures for certain applications which require high performance, low energy, and reconfigurable solutions.…”

Section: Related Workmentioning

confidence: 99%

“…The challenges become more stringent for vision sensors under certain environmental conditions, e.g., rain and horizontal obscuration. [8][9][10] Therefore, using field-programmable gate array (FPGA) for processing is a suitable choice for the handling of parallel processes because of the inherited parallelism. 4,5 To meet these challenges, there is an interest in augmenting vision sensors with beyond-vision-range sensors such as lasers and thermal sensors.…”

Section: Introductionmentioning

confidence: 99%

“…11 • Acquire images, process them and transmit feature information to a client device where analysis is performed [ Fig. 8 In comparison to the aforementioned two approaches, our approach, shown in Fig. 12,13 In the first approach, the computational load on the node is minimal but the communication requirement is enormous, which increases communication latency.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Exploration of preprocessing architectures for field-programmable gate array-based thermal-visual smart camera

Imran

Rinner

Zand

et al. 2016

J. Electron. Imaging

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Nils, "Exploration of preprocessing architectures for field-programmable gate array-based thermal-visual smart camera," Abstract. 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.

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Section: Problem Descriptionmentioning

confidence: 99%

Section: Problem Descriptionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exploration of preprocessing architectures for field-programmable gate array-based thermal-visual smart camera

Imran

Rinner

Zand

et al. 2016

J. Electron. Imaging

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Communication and computation inter-effects in people counting using intelligence partitioning

Shallari

Krug

O’Nils

2020

J Real-Time Image Proc

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The rapid development of the Internet of Things is affecting the requirements towards wireless vision sensor networks (WVSN). Future smart camera architectures require battery-operated devices to facilitate deployment for scenarios such as industrial monitoring, environmental monitoring and smart city, consequently imposing constraints on the node energy consumption. This paper provides an analysis of the inter-effects between computation and communication energy for a smart camera node. Based on a people counting scenario, we evaluate the trade-off for the node energy consumption with different processing configurations of the image processing tasks, and several communication technologies. The results indicate that the optimal partition between the smart camera node and remote processing is with background modelling, segmentation, morphology and binary compression implemented in the smart camera, supported by Bluetooth Low Energy (BLE) version 5 technologies. The comparative assessment of these results with other implementation scenarios underlines the energy efficiency of this approach. This work changes pre-conceptions regarding design space exploration in WVSN, motivating further investigation regarding the inclusion of intermediate processing layers between the node and the cloud to interlace low-power configurations of communication and processing architectures.

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A new image size reduction model for an efficient visual sensor network

Kaljahi

Shivakumara

Idris

et al. 2019

Journal of Visual Communication and Image Representation

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Image size reduction for energy-efficient transmission without losing quality is critical in Visual Sensor Networks (VSNs). The proposed method finds overlapping regions using camera locations, which eliminate unfocussed regions from the input images. The sharpness for the overlapped regions is estimated to find the Dominant Overlapping Region (DOR). The proposed model partitions further the DOR into sub-DORs according to capacity of the cameras. To reduce noise effects from the sub-DOR, we propose to perform a Median operation, which results in a Compressed Significant Region (CSR). For non-DOR, we obtain Sobel edges, which reduces the size of the images down to ambinary form. The CSR and Sobel edges of the non-DORs are sent by a VSN. Experimental results and a comparative study with the state-of-the-art methods shows that the proposed model outperforms the existing methods in terms of quality, energy consumption and network lifetime.

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Architecture of wireless Visual Sensor Node with Region of Interest coding

Cited by 7 publications

References 13 publications

Exploration of preprocessing architectures for field-programmable gate array-based thermal-visual smart camera

Exploration of preprocessing architectures for field-programmable gate array-based thermal-visual smart camera

Communication and computation inter-effects in people counting using intelligence partitioning

A new image size reduction model for an efficient visual sensor network

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