Tag: image sequences
A Low Power VLSI Architecture for Mesh-based Video Motion Tracking
This paper proposes a low-power very large-scale integration (VLSI) architecture for motion tracking. It uses a hierarchical adaptive structured mesh that generates a content-based video representation. The proposed mesh is a coarse-to-fine hierarchical two-dimensional mesh that is formed by recursive triangulation of the initial coarse mesh geometry. The structured mesh offers a significant reduction in the number of bits that describe the mesh topology. The motion of the mesh nodes represents the deformation of the video object. The architecture consists of motion estimation and motion compensation units. The motion estimation architecture generates a progressive mesh code and the motion vectors of the mesh nodes. It reduces the power consumption, uses a simpler approach for mesh construction, approximates the mesh nodes motion vector by using the three step search algorithm and uses a parallel motion estimation core to evaluate the mesh nodes motion vectors. Moreover, it maximizes the lifetime of the internal buffers. The motion compensation architecture uses a multiplication-free algorithm for affine transformation, which significantly reduces the complexity of the motion compensation architecture. Moreover, using pipelined affine units contributes to the power savings. The video motion compensation architecture processes a reference frame, mesh nodes and motion vectors to predict a video frame. It implements parallel threads in which each thread implements a pipelined chain of scalable affine units. This motion compensation algorithm allows the use of one simple warping unit to map a hierarchical structure. The affine unit warps the texture of a patch at any level of hierarchical mesh independently. The processor uses a memory serialization unit, which interfaces the memory to the parallel units. The architecture has been prototyped using top-down low-power design methodology. The performance analysis shows that this processor can be used in online object-based video applications such as in MPEG and VRML.
Published in:
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on (Volume:49 , Issue: 7 )
- Page(s):
- 488 – 504
- ISSN :
- 1057-7130
- INSPEC Accession Number:
- 7460367
- DOI:
- 10.1109/TCSII.2002.805248
- Date of Publication :
- Jul 2002
- Date of Current Version :
- 10 December 2002
- Issue Date :
- Jul 2002
- Sponsored by :
- IEEE Circuits and Systems Society
- Publisher:
- IEEE
Wael Badawy and Magdy Bayoumi, “A Low Power VLSI Architecture for Mesh-based Video Motion Tracking,” The IEEE Transactions on Circuits and Systems II, Vol. 49, July 2002, pp. 488-504.
Architectures for Finite Radon Transform
Two VLSI architectures for the finite Radon transform are presented. The first is a reference architecture using memory blocks and the second is a memoryless architecture. The proposed architectures use 7×7 size image blocks and are prototyped for processing the CIF image sequence. The simulation and synthesis results show that the core speeds of the two proposed architectures are around 100 and 82 MHz, respectively.
Published in:
Electronics Letters (Volume:40 , Issue: 15 )
- Page(s):
- 931 – 932
- ISSN :
- 0013-5194
- INSPEC Accession Number:
- 8068176
- DOI:
- 10.1049/el:20040566
- Date of Publication :
- 22 July 2004
- Date of Current Version :
- 02 August 2004
- Issue Date :
- 22 July 2004
- Sponsored by :
- Institution of Engineering and Technology
- Publisher:
- IET
C. A. Rahman and W. Badawy, “Architectures for Finite Radon Transform“, The IEE Electronics Letters, Vol. 40, Issue 15, July 2004, pp. 931-932.
Automatic License Plate Recognition (ALPR): A State-of-the-Art Review
Abstract:
Automatic license plate recognition (ALPR) is the extraction of vehicle license plate information from an image or a sequence of images. The extracted information can be used with or without a database in many applications, such as electronic payment systems (toll payment, parking fee payment), and freeway and arterial monitoring systems for traffic surveillance. The ALPR uses either a color, black and white, or infrared camera to take images. The quality of the acquired images is a major factor in the success of the ALPR. ALPR as a real-life application has to quickly and successfully process license plates under different environmental conditions, such as indoors, outdoors, day or night time. It should also be generalized to process license plates from different nations, provinces, or states. These plates usually contain different colors, are written in different languages, and use different fonts; some plates may have a single color background and others have background images. The license plates can be partially occluded by dirt, lighting, and towing accessories on the car. In this paper, we present a comprehensive review of the state-of-the-art techniques for ALPR. We categorize different ALPR techniques according to the features they used for each stage, and compare them in terms of pros, cons, recognition accuracy, and processing speed. Future forecasts of ALPR are given at the end.
Published in:
Circuits and Systems for Video Technology, IEEE Transactions on (Volume:23 , Issue: 2 )
- Page(s):
- 311 – 325
- ISSN :
- 1051-8215
- INSPEC Accession Number:
- 13270696
- DOI:
- 10.1109/TCSVT.2012.2203741
- Date of Publication :
- 07 June 2012
- Date of Current Version :
- 01 February 2013
- Issue Date :
- Feb. 2013
- Sponsored by :
- IEEE Circuits and Systems Society
- Publisher:
- IEEE
- Download the paper here Automatic License Plate Recognition (ALPR): A State-of-the-Art Review
Link to the list of other Peer Journal Publications
Reference: Shan Du; Ibrahim, M.; Shehata, M.; Badawy, W., “Automatic License Plate Recognition (ALPR): A State-of-the-Art Review,” IEEE Transactions on Circuits and Systems for Video Technology, vol.23, no.2, pp.311,325, Feb. 2013.
A Low Power VLSI Architecture for Mesh-based Video Motion Tracking
This paper proposes a low-power very large-scale integration (VLSI) architecture for motion tracking. It uses a hierarchical adaptive structured mesh that generates a content-based video representation. The proposed mesh is a coarse-to-fine hierarchical two-dimensional mesh that is formed by recursive triangulation of the initial coarse mesh geometry. The structured mesh offers a significant reduction in the number of bits that describe the mesh topology. The motion of the mesh nodes represents the deformation of the video object. The architecture consists of motion estimation and motion compensation units. The motion estimation architecture generates a progressive mesh code and the motion vectors of the mesh nodes. It reduces the power consumption, uses a simpler approach for mesh construction, approximates the mesh nodes motion vector by using the three step search algorithm and uses a parallel motion estimation core to evaluate the mesh nodes motion vectors. Moreover, it maximizes the lifetime of the internal buffers. The motion compensation architecture uses a multiplication-free algorithm for affine transformation, which significantly reduces the complexity of the motion compensation architecture. Moreover, using pipelined affine units contributes to the power savings. The video motion compensation architecture processes a reference frame, mesh nodes and motion vectors to predict a video frame. It implements parallel threads in which each thread implements a pipelined chain of scalable affine units. This motion compensation algorithm allows the use of one simple warping unit to map a hierarchical structure. The affine unit warps the texture of a patch at any level of hierarchical mesh independently. The processor uses a memory serialization unit, which interfaces the memory to the parallel units. The architecture has been prototyped using top-down low-power design methodology. The performance analysis shows that this processor can be used in online object-based video applications such as in MPEG and VRML.
Published in:
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on (Volume:49 , Issue: 7 )
- Page(s):
- 488 – 504
- ISSN :
- 1057-7130
- INSPEC Accession Number:
- 7460367
- DOI:
- 10.1109/TCSII.2002.805248
- Date of Publication :
- Jul 2002
- Date of Current Version :
- 10 December 2002
- Issue Date :
- Jul 2002
- Sponsored by :
- IEEE Circuits and Systems Society
- Publisher:
- IEEE
Wael Badawy and Magdy Bayoumi, “A Low Power VLSI Architecture for Mesh-based Video Motion Tracking,” The IEEE Transactions on Circuits and Systems II, Vol. 49, July 2002, pp. 488-504.
Architectures for Finite Radon Transform
Two VLSI architectures for the finite Radon transform are presented. The first is a reference architecture using memory blocks and the second is a memoryless architecture. The proposed architectures use 7×7 size image blocks and are prototyped for processing the CIF image sequence. The simulation and synthesis results show that the core speeds of the two proposed architectures are around 100 and 82 MHz, respectively.
Published in:
Electronics Letters (Volume:40 , Issue: 15 )
- Page(s):
- 931 – 932
- ISSN :
- 0013-5194
- INSPEC Accession Number:
- 8068176
- DOI:
- 10.1049/el:20040566
- Date of Publication :
- 22 July 2004
- Date of Current Version :
- 02 August 2004
- Issue Date :
- 22 July 2004
- Sponsored by :
- Institution of Engineering and Technology
- Publisher:
- IET
C. A. Rahman and W. Badawy, “Architectures for Finite Radon Transform“, The IEE Electronics Letters, Vol. 40, Issue 15, July 2004, pp. 931-932.
Automatic License Plate Recognition (ALPR): A State-of-the-Art Review
Abstract:
Automatic license plate recognition (ALPR) is the extraction of vehicle license plate information from an image or a sequence of images. The extracted information can be used with or without a database in many applications, such as electronic payment systems (toll payment, parking fee payment), and freeway and arterial monitoring systems for traffic surveillance. The ALPR uses either a color, black and white, or infrared camera to take images. The quality of the acquired images is a major factor in the success of the ALPR. ALPR as a real-life application has to quickly and successfully process license plates under different environmental conditions, such as indoors, outdoors, day or night time. It should also be generalized to process license plates from different nations, provinces, or states. These plates usually contain different colors, are written in different languages, and use different fonts; some plates may have a single color background and others have background images. The license plates can be partially occluded by dirt, lighting, and towing accessories on the car. In this paper, we present a comprehensive review of the state-of-the-art techniques for ALPR. We categorize different ALPR techniques according to the features they used for each stage, and compare them in terms of pros, cons, recognition accuracy, and processing speed. Future forecasts of ALPR are given at the end.
Published in:
Circuits and Systems for Video Technology, IEEE Transactions on (Volume:23 , Issue: 2 )
- Page(s):
- 311 – 325
- ISSN :
- 1051-8215
- INSPEC Accession Number:
- 13270696
- DOI:
- 10.1109/TCSVT.2012.2203741
- Date of Publication :
- 07 June 2012
- Date of Current Version :
- 01 February 2013
- Issue Date :
- Feb. 2013
- Sponsored by :
- IEEE Circuits and Systems Society
- Publisher:
- IEEE
- Download the paper here Automatic License Plate Recognition (ALPR): A State-of-the-Art Review
Link to the list of other Peer Journal Publications
Reference: Shan Du; Ibrahim, M.; Shehata, M.; Badawy, W., “Automatic License Plate Recognition (ALPR): A State-of-the-Art Review,” IEEE Transactions on Circuits and Systems for Video Technology, vol.23, no.2, pp.311,325, Feb. 2013.