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Sökning: WFRF:(O'Nils Mattias)

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51.
  • Imran, Muhammad, et al. (författare)
  • Complexity Analysis of Vision Functions for Comparison of Wireless Smart Cameras
  • 2014
  • Ingår i: International Journal of Distributed Sensor Networks. - : SAGE Publications. - 1550-1329 .- 1550-1477. ; , s. Art. no. 710685-
  • Tidskriftsartikel (refereegranskat)abstract
    • There are a number of challenges caused by the large amount of data and limited resources such as memory, processing capability, energy consumption, and bandwidth, when implementing vision systems on wireless smart cameras using embedded platforms. It is usual for research in this field to focus on the development of a specific solution for a particular problem. There is a requirement for a tool which facilitates the complexity estimation and comparison of wireless smart camera systems in order to develop efficient generic solutions. To develop such a tool, we have presented, in this paper, a complexity model by using a system taxonomy. In this model, we have investigated the arithmetic complexity and memory requirements of vision functions with the help of system taxonomy. To demonstrate the use of the proposed model, a number of actual systems are analyzed in a case study. The complexity model, together with system taxonomy, is used for the complexity estimation of vision functions and for a comparison of vision systems. After comparison, the systems are evaluated for implementation on a single generic architecture. The proposed approach will assist researchers in benchmarking and will assist in proposing efficient generic solutions for the same class of problems with reduced design and development costs.
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52.
  • Imran, Muhammad, et al. (författare)
  • Complexity Analysis of Vision Functions for implementation of Wireless Smart Cameras using System Taxonomy
  • 2012
  • Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - Belgium : SPIE - International Society for Optical Engineering. - 9780819491299 ; , s. Art. no. 84370C-
  • Konferensbidrag (refereegranskat)abstract
    • There are a number of challenges caused by the large amount of data and limited resources such as memory, processing capability, energy consumption and bandwidth when implementing vision systems on wireless smart cameras using embedded platforms. It is usual for research in this field to focus on the development of a specific solution for a particular problem. There is a requirement for a tool which has the ability to predict the resource requirements for the development and comparison of vision solutions in wireless smart cameras. To accelerate the development of such tool, we have used a system taxonomy, which shows that the majority of wireless smart cameras have common functions. In this paper, we have investigated the arithmetic complexity and memory requirements of vision functions by using the system taxonomy and proposed an abstract complexity model. To demonstrate the use of this model, we have analysed a number of implemented systems with this model and showed that complexity model together with system taxonomy can be used for comparison and generalization of vision solutions. Moreover, it will assist researchers/designers to predict the resource requirements for different class of vision systems in a reduced time and which will involve little effort. 
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53.
  • Imran, Muhammad, et al. (författare)
  • Demo: SRAM FPGA based Wireless Smart Camera: SENTIOF-CAM
  • 2014
  • Ingår i: Proceedings of the International Conference on Distributed Smart Cameras. - New York, NY, USA : ACM. - 9781450329255
  • Konferensbidrag (refereegranskat)abstract
    • Wireless Sensor Networks applications with huge amount of datarequirements are attracting the utilization of high performanceembedded platforms i.e. Field Programmable Gate Arrays(FPGAs) for in-node sensor processing. However, the designcomplexity, high configuration and static energies of SRAMFPGAs impose challenges for duty cycled applications. In thisdemo, we demonstrate the functionality of SRAM FPGA basedwireless vision sensor node called SENTIOF-CAM. Thedemonstration shows that by using intelligent techniques, a lowenergy and low complexity SRAM FPGA based wireless visionsensor node can be realized for duty cycled applications.
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54.
  • Imran, Muhammad, et al. (författare)
  • Energy Driven Selection and Hardware Implementation of Bi-Level Image Compression
  • 2014
  • Ingår i: Proceedings of the International Conference on Distributed Smart Cameras. - New York, NY, USA : ACM Press. - 9781450329255
  • Konferensbidrag (refereegranskat)abstract
    • Wireless Vision Sensor Nodes are considered to have smaller resources and are expected to have a longer lifetime based on the available limited energy. A wireless Vision Sensor Node (VSN) is often characterized to consume more energy in communication as compared to processing. The communication energy can be reduced by reducing the amount of transmission data with the help of a suitable compression scheme. This work investigates bi-level compression schemes including G4, G3, JBIG2, Rectangular, GZIP, GZIP_Pack and JPEG-LS on a hardware platform. The investigation results show that GZIP_pack, G4 and JBIG2 schemes are suitable for a hardware implemented VSN. JBIG2 offers up to a 43 percent reduction in overall energy consumption as compared to G4 and GZIP_pack for complex images. However, JBIG2 has higher resource requirement and implementation complexity. The difference in overall energy consumption is smaller for smooth images. Depending on the application requirement, the exclusion of a header can reduce the energy consumption by approximately 1 to 33 percent.
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55.
  • Imran, Muhammad, et al. (författare)
  • Energy Efficient SRAM FPGA based Wireless Vision Sensor Node: SENTIOF‐CAM
  • 2014
  • Ingår i: IEEE transactions on circuits and systems for video technology (Print). - 1051-8215 .- 1558-2205. ; 24:12, s. 2132-2143
  • Tidskriftsartikel (refereegranskat)abstract
    • Many Wireless Vision Sensor Networks (WVSNs) applications are characterized to have a low duty cycling. An individual wireless Vision Senor Node (VSN) in WVSN is required to operate with limited resources i.e., processing, memory and wireless bandwidth on available limited energy. For such resource constrained VSN, this paper presents a low complexity, energy efficient and programmable VSN architecture based on a design matrix which includes partitioning of processing load between the node and a server, a low complexity background subtraction, bi-level video coding and duty cycling. The tasks partitioning and proposed background subtraction reduces the processing energy and design complexity for hardware implemented VSN. The bi-level video coding reduces the communication energy whereas the duty cycling conserves energy for lifetime maximization. The proposed VSN, referred to as SENTIOF-CAM, has been implemented on a customized single board, which includes SRAM FPGA, microcontroller, radio transceiver and a FLASH memory. The energy values are measured for different states and results are compared with existing solutions. The comparison shows that the proposed solution can offer up to 69 times energy reduction. The lifetime based on measured energy values shows that for a sample period of 5 minutes, a 3.2 years lifetime can be achieved with a battery of 37.44 kJ energy. In addition to this, the proposed solution offers generic architecture with smaller design complexity on a hardware reconfigurable platform and offers easy adaptation for a number of applications.
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56.
  • Imran, Muhammad, et al. (författare)
  • Exploration of preprocessing architectures for field-programmable gate array-based thermal-visual smart camera
  • 2016
  • Ingår i: Journal of Electronic Imaging (JEI). - 1017-9909 .- 1560-229X. ; 25:4
  • Tidskriftsartikel (refereegranskat)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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57.
  • Imran, Muhammad, et al. (författare)
  • Implementation of wireless Vision Sensor Node for Characterization of Particles in Fluids
  • 2012
  • Ingår i: IEEE transactions on circuits and systems for video technology (Print). - 1051-8215 .- 1558-2205. ; 22:11, s. 1634-1643
  • Tidskriftsartikel (refereegranskat)abstract
    • Wireless Vision Sensor Networks (WVSNs) have a number of wireless Vision Sensor Nodes (VSNs), often spread over a large geographical area. Each node has an image capturing unit, a battery or alternative energy source, a memory unit, a light source, a wireless link and a processing unit. The challenges associated with WVSNs include low energy consumption, low bandwidth, limited memory and processing capabilities. In order to meet these challenges, our research is focused on the exploration of energy efficient reconfigurable architectures for VSN. In this work, the design/research challenges associated with the implementation of VSN on different computational platforms such as micro-controller, FPGA and server, are explored. In relation to this, the effect on the energy consumption and the design complexity at the node, when the functionality is moved from one platform to another are analyzed. Based on the implementation of the VSN on embedded platforms, the lifetime of the VSN is predicted using the measured energy values of the platforms for different implementation strategies. The implementation results show that an architecture, where the compressed images after pixel based operation are transmitted, realize a WVSN system with low energy consumption. Moreover, the complex post processing tasks are moved to a server, with reduced constraints. 
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58.
  • Imran, Muhammad, et al. (författare)
  • Implementation of Wireless Vision Sensor Node With a Lightweight Bi-Level Video Coding
  • 2013
  • Ingår i: IEEE Journal on Emerging and Selected Topics in Circuits and Systems. - : IEEE Press. - 2156-3357 .- 2156-3365. ; 3:2, s. 198-209
  • Tidskriftsartikel (refereegranskat)abstract
    • Wireless vision sensor networks (WVSNs) consist ofa number of wireless vision sensor nodes (VSNs) which have limitedresources i.e., energy, memory, processing, and wireless bandwidth.The processing and communication energy requirements ofindividual VSN have been a challenge because of limited energyavailability. To meet this challenge, we have proposed and implementeda programmable and energy efficient VSN architecturewhich has lower energy requirements and has a reduced designcomplexity. In the proposed system, vision tasks are partitionedbetween the hardware implemented VSN and a server. The initialdata dominated tasks are implemented on the VSN while thecontrol dominated complex tasks are processed on a server. Thisstrategy will reduce both the processing energy consumption andthe design complexity. The communication energy consumption isreduced by implementing a lightweight bi-level video coding on theVSN. The energy consumption is measured on real hardware fordifferent applications and proposed VSN is compared against publishedsystems. The results show that, depending on the application,the energy consumption can be reduced by a factor of approximately1.5 up to 376 as compared to VSN without the bi-level videocoding. The proposed VSN offers energy efficient, generic architecturewith smaller design complexity on hardware reconfigurableplatform and offers easy adaptation for a number of applicationsas compared to published systems.
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59.
  • Imran, Muhammad (författare)
  • Investigation of Architectures for Wireless Visual Sensor Nodes
  • 2011
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Wireless visual sensor network is an emerging field which has proveduseful in many applications, including industrial control and monitoring,surveillance, environmental monitoring, personal care and the virtual world.Traditional imaging systems used a wired link, centralized network, highprocessing capabilities, unlimited storage and power source. In manyapplications, the wired solution results in high installation and maintenancecosts. However, a wireless solution is the preferred choice as it offers lessmaintenance, infrastructure costs and greater scalability.The technological developments in image sensors, wirelesscommunication and processing platforms have paved the way for smartcamera networks usually referred to as Wireless Visual Sensor Networks(WVSNs). WVSNs consist of a number of Visual Sensor Nodes (VSNs)deployed over a large geographical area. The smart cameras can performcomplex vision tasks using limited resources such as batteries or alternativeenergy sources, embedded platforms, a wireless link and a small memory.Current research in WVSNs is focused on reducing the energyconsumption of the node so as to maximise the life of the VSN. To meet thischallenge, different software and hardware solutions are presented in theliterature for the implementation of VSNs.The focus in this thesis is on the exploration of energy efficientreconfigurable architectures for VSNs by partitioning vision tasks on software,hardware platforms and locality. For any application, some of the vision taskscan be performed on the sensor node after which data is sent over the wirelesslink to the server where the remaining vision tasks are performed. Similarly,at the VSN, vision tasks can be partitioned on software and the hardwareplatforms.In the thesis, all possible strategies are explored, by partitioning visiontasks on the sensor node and on the server. The energy consumption of thesensor node is evaluated for different strategies on software platform. It isobserved that performing some of the vision tasks on the sensor node andsending compressed images to the server where the remaining vision tasks areperformed, will have lower energy consumption.In order to achieve better performance and low power consumption,Field Programmable Gate Arrays (FPGAs) are introduced for theimplementation of the sensor node. The strategies with reasonable designtimes and costs are implemented on hardware-software platform. Based onthe implementation of the VSN on the FPGA together with micro-controller,the lifetime of the VSN is predicted using the measured energy values of theplatforms for different processing strategies. The implementation resultsprove our analysis that a VSN with such characteristics will result in a longerlife time.
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60.
  • Imran, Muhammad, et al. (författare)
  • Low Complexity Background Subtraction for Wireless Vision Sensor Node
  • 2013
  • Ingår i: Proceedings - 16th Euromicro Conference on Digital System Design, DSD 2013. - 9780769550749 ; , s. 681-688
  • Konferensbidrag (refereegranskat)abstract
    • Wireless vision sensor nodes consist of limited resources such as energy, memory, wireless bandwidth and processing. Thus it becomes necessary to investigate lightweight vision tasks. To highlight the foreground objects, many machine vision applications depend on the background subtraction technique. Traditional background subtraction approaches employ recursive and non-recursive techniques and store the whole image in memory. This raises issues like complexity on hardware platform, energy requirements and latency. This work presents a low complexity background subtraction technique for a hardware implemented VSN. The proposed technique utilizes existing image scaling techniques for scaling down the image. The downscaled image is stored in memory of microcontroller which is already there for transmission. For subtraction operation, the background pixels are generated in real time through up scaling. The performance, and memory requirements of the system is compared for four image scaling techniques including nearest neighbor, averaging, bilinear, and bicubic. The results show that a system with lightweight scaling techniques, i.e., nearest neighbor and averaging, up to a scaling factor of 8, missed on average less than one object as compared to a system which uses a full original background image. The proposed approach will reduce the cost, design/implementation complexity and the memory requirement by a factor of up to 64.
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