FPGA architecture for static background subtraction in real time

Oliveira, Jozias Parente de; Printes, André; Freire, R.C.S.; Melcher, Elmar U. K.; Silva, Ivan S. S.

doi:10.1145/1150343.1150356

Cited by 13 publications

(14 citation statements)

References 7 publications

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“…Hence, for a fair comparison, Table I reports synthesis results of the proposed architecture for the same Altera FPGAs. Clearly, the proposed architecture requires [10] and [11]. It has a maximum frequency of operation (Fmax) of 125.4MHz on Altera Cyclone III, the highest reported so far, due to its multiplier free and optimized hardware architecture.…”

Section: Object Extractionmentioning

confidence: 99%

“…The proposed object extraction scheme, consisting of background subtraction, row/column scanning and threshold comparison blocks, was implemented and tested on various FPGAs. Table I compares the proposed architecture with [10] and [11], which have reported synthesis results for similar object extraction functions. Both [10] and [11] have used Altera FPGAs to synthesise their architectures.…”

Section: Object Extractionmentioning

confidence: 99%

“…Table I compares the proposed architecture with [10] and [11], which have reported synthesis results for similar object extraction functions. Both [10] and [11] have used Altera FPGAs to synthesise their architectures. Hence, for a fair comparison, Table I reports synthesis results of the proposed architecture for the same Altera FPGAs.…”

Section: Object Extractionmentioning

confidence: 99%

See 2 more Smart Citations

Image Transmission in Wireless Sensor Networks

Biradar¹

2014

IJRET

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Section: Object Extractionmentioning

confidence: 99%

Section: Object Extractionmentioning

confidence: 99%

Section: Object Extractionmentioning

confidence: 99%

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Image Transmission in Wireless Sensor Networks

Biradar¹

2014

IJRET

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“…In the paper [29], foreground object detection using background subtraction was presented. The background was modeled statistically using pixel-by-pixel basis-a single pixel was modeled by the expected colour value, the standard deviation of colour value, the variation of brightness distortion and the variation of chromaticity distortion.…”

Section: Introductionmentioning

confidence: 99%

Real-time background generation and foreground object segmentation for high-definition colour video stream in FPGA device

Kryjak

Komorkiewicz

Gorgon

2012

J Real-Time Image Proc

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The processing of a high-definition video stream in real-time is a challenging task for embedded systems. However, modern FPGA devices have both a high operating frequency and sufficient logic resources to be successfully used in these tasks. In this article, an advanced system that is able to generate and maintain a complex background model for a scene as well as segment the foreground for an HD colour video stream (1,920 9 1,080 @ 60 fps) in real-time is presented. The possible application ranges from video surveillance to machine vision systems. That is, in all cases, when information is needed about which objects are new or moving in the scene. Excellent results are obtained by using the CIE Lab colour space, advanced background representation as well as integrating information about lightness, colour and texture in the segmentation step. Finally, the complete system is implemented in a single high-end FPGA device.

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“…Graphics hardware has recently been used to achieve real-time performance. In [14], [15], field programmable gate arrays are used to imCopyright c 2011 The Institute of Electronics, Information and Communication Engineers plement algorithms based on background subtraction. However, restrictions on the architecture still hinder effective performance.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Object Detection Using Adaptive Background Model and Margined Sign Correlation

Yamamoto

Iwai

Ishiguro

2011

IEICE Trans. Inf. & Syst.

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Ayaka YAMAMOTO†a) , Nonmember, Yoshio IWAI †b) , and Hiroshi ISHIGURO †c) , Members SUMMARYBackground subtraction is widely used in detecting moving objects; however, changing illumination conditions, color similarity, and real-time performance remain important problems. In this paper, we introduce a sequential method for adaptively estimating background components using Kalman filters, and a novel method for detecting objects using margined sign correlation (MSC). By applying MSC to our adaptive background model, the proposed system can perform object detection robustly and accurately. The proposed method is suitable for implementation on a graphics processing unit (GPU) and as such, the system realizes real-time performance efficiently. Experimental results demonstrate the performance of the proposed system.

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FPGA architecture for static background subtraction in real time

Cited by 13 publications

References 7 publications

Image Transmission in Wireless Sensor Networks

Image Transmission in Wireless Sensor Networks

Real-time background generation and foreground object segmentation for high-definition colour video stream in FPGA device

Real-Time Object Detection Using Adaptive Background Model and Margined Sign Correlation

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