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A hardware-efficient high performance digital architecture for run-time computation of normalized cross correlation

WSEAS Transactions on Circuits and Systems 2006年第9期5卷 1416-1423页

作者： Zhang, Ming Z. Asari, Vijayan K. Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University 231 Kaufman Hall Norfolk VA 23529 United States

A novel architecture for performing high speed computation of normalized cross correlation (NCC) is proposed in this paper. The approach promotes the concept of digital filter design to simplify window related operations and log-domain computations to eliminate all multiplications, divisions, squares, and square-roots utilizing the approximation techniques for efficient estimation of log2 and inverse-log2. The new design is capable of performing run-time calculation of NCC and the energy normalization on the fly, eliminating the frame buffering and frame sized integral tables. A new concept of uniform filter design is also presented to reduce the number of processing element arrays (PEAs) from V PEAs to 2 PEAs for a U × V window. This concept is applied to simplify the calculation of average value and energy in NCC equation. It is observed that the performance of the system with parallel pipelined architecture is able to achieve 178.5 million outputs per second (MOPS), or equivalently 142.8 billion multiplications per second, on Xilinx's Virtex II XC2V6000-4ff1152 FPGA with maximum clock frequency of 178.5MHz with 20 × 20 feature template of 8-bit resolution. Given a 1024 × 1024 data frame, the system can process over 170 frames per second (fps). Similarly, the improved full precision logarithmic module is able to sustain 212.2 MOPS at 212.2MHz maximum clock frequency with 32-bit resolution.

关键词： Digital filters

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Design of an efficient multiplier-less architecture for multi-dimensional convolution

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10th Asia-Pacific Conference on Advances in computer Systems Architecture, ACSAC 2005

作者： Zhang, Ming Z. Ngo, Hau T. Asari, Vijayan K. Computer Vision and Machine Intelligence Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA 23529 United States

ISBN: (纸本)3540296433

Design of a hardware efficient multiplier-less architecture for the computation of multi-dimensional convolution is presented in this paper. The new architecture performs computations in the logarithmic domain by utilizing novel multiplier-less log2 and inverse-loga modules. An effective data handling strategy is developed in conjunction with the logarithmic modules to eliminate the necessity of multipliers in the architecture. The proposed approach reduces hardware resources significantly compared to other approaches while it still maintains a high degree of accuracy. The architecture is developed as a combined systolic-pipelined design that produces an output in every clock cycle after the initial latency of the system. The architecture is capable of operating with a high speed clock frequency of 99 MHz based on Xilinx's Virtex II 2v2000ff896-4 FPGA and the throughput of the system is observed as 99 MOPS (million outputs per second). © Springer-Verlag Berlin Heidelberg 2005.

关键词： computer architecture

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On using an associative memory for improving digital color images: Color characterization, enhancement, and color balancing

On using an associative memory for improving digital color i...

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International Joint Conference on Neural Networks, IJCNN 2005

作者： Seow, Ming-Jung Asari, Vijayan K. Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA 23529

Actual observed scenes usually produce a wide dynamic range. Currently available visual systems use low dynamic range light detector that provide only 8 bits of brightness information at each pixel. This greatly limits what visual systems can do for surveillance applications such as face detection and face recognition. A color image enhancement procedure based on the concept of color characterization, enhancement, and color balancing is proposed in this paper. The enhancement technique directly operates on pixels using a hyperbolic tangent function to increase the dynamic range of the pixel. The global and local statistics of the image is used to control the curvature of the hyperbolic tangent function. The color characterization and color balancing processes are based on a new nonlinear line attractor network to create a color manifold to restore the relationship of red, green, and blue components of the pixels. The proposed enhancement approach greatly improves the dynamic range compression and color rendition of an image. © 2005 IEEE.

关键词： Color image processing

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A robust image enhancement technique for improving image visual quality in shadowed scenes

A robust image enhancement technique for improving image vis...

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4th International Conference on Image and Video Retrieval, CIVR 2005

作者： Tao, Li Asari, Vijayan K. Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA 23529 United States

An effective and robust image enhancement algorithm is presented for improving the visual quality of digital images captured under extremely low or non-uniform lighting conditions. The proposed algorithm is composed of two separated processes viz. adaptive luminance enhancement and adaptive contrast enhancement to provide a more flexible and better control over the image enhancement. Adaptive luminance enhancement is an intensity transformation based on a specifically designed nonlinear transfer function which largely increases the luminance of darker pixels and compresses the dynamic range as well. Adaptive contrast enhancement adjusts the intensity of each pixel based on its relative magnitude with respect to the neighboring pixels. Both processes can be self-tuned by the image statistical information. A proportional color restoration process is applied to convert the enhanced intensity image back to a color image. Real time processing and embedded application in mobile device have been successfully realized. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image enhancement

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A visibility improvement system for low vision drivers by nonlinear enhancement of fused visible and infrared video

A visibility improvement system for low vision drivers by no...

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2005 IEEE computer Society Conference on computer vision and Pattern Recognition, CVPR 2005 - Workshops

作者： Ngo, Hau Tao, Li Zhang, Ming Livingston, Adam Asari, Vijayan Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University NorfolkVA23529 United States

ISBN: (纸本)0769526608

Development of a visibility improvement system for helping drivers with poor vision during night and bad weather conditions is proposed in this paper. Video streams captured by a CCD camera and an infrared camera are registered and fused to obtain image details in extremely low lighting conditions. A novel image enhancement technique employing a nonlinear expansion function is developed for enhancing the fused images. The slope characteristics of the expansion function at an individual pixel location is based on the statistical properties of its neighborhood pixels. The expansion function is also capable of reducing the intensity of the overly bright image regions due to the presence of head lights from vehicles in opposite direction. The enhanced video stream is then subjected to a color restoration process to introduce natural color using the color information gathered from the CCD camera image. The entire image processing and analysis system is being installed in an FPGA environment for performing the processing in real-time. The processed video stream is displayed on a Head-Up Display located directly in front of the driver to assist him/her to drive safely in poor visibility environments. Preliminary results obtained in various experiments conducted with the proposed system are encouraging. © 2005 IEEE computer Society. All rights reserved.

关键词： CCD cameras

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A multi-view approach on modular PCA for illumination and pose invariant face recognition

A multi-view approach on modular PCA for illumination and po...

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33rd Applied Imagery Pattern Recognition Workshop

作者： Sankaran, Praveen Asari, Vijayan Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA 23529-0246 United States

ISBN: (纸本)0769522505

A modified approach on Modular PCA for face recognition is presented in this paper. The proposed changes aim to improve the recognition rates for modular PCA for face images with large variation in light and facial expression. The eyes form one of the most invariant regions on the face. A sub-image from this region is considered. Weight vectors from this region are appended to the existing weight vector for Modular PCA. The accuracies for the modified method, the original method and PCA method are evaluated under conditions of varying pose, illumination and expressions using standard face databases. © 2005 IEEE.

关键词： Face recognition

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On using an associative memory for improving digital color images: color characterization, enhancement, and color balancing

On using an associative memory for improving digital color i...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ming-Jung Seow V.K. Asari Computational Intelligence & Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

关键词： Associative memory Color Dynamic range Visual system Layout Brightness Surveillance Face detection Face recognition Statistics

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A multisensor image fusion and enhancement system for assisting drivers in poor lighting conditions

A multisensor image fusion and enhancement system for assist...

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Applied Imagery Pattern Recognition Workshop (AIPR)

作者： Li Tao Hau Ngo Ming Zhang A. Livingston V. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

A system of multisensor image fusion and enhancement for visibility improvement is proposed in this paper for helping drivers driving at night or under bad weather conditions. Video stream captured by a CCD camera is enhanced, then aligned and fused with another stream captured by a thermal camera to improve the visibility of roads in extremely low lighting conditions. A nonlinear image enhancement technique capable of dynamic range compression and contrast enhancement is developed to enhance the visible images prior to fusion. The thermal image and the enhanced visible image are then aligned based on prior information obtained on image registration process. Pixel-level multiresolution based image fusion method is applied to merge source images. After image fusion, a color restoration is performed on fused images with the chromatic information of visible images. The entire image processing and analysis system is being installed in an FPGA environment. Preliminary results obtained in various experiments conducted with the proposed system are encouraging

关键词： Image fusion Streaming media Charge-coupled image sensors Video compression Charge coupled devices Roads Image enhancement Dynamic range Image coding Image registration

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A Visibility Improvement System for Low vision Drivers by Nonlinear Enhancement of Fused Visible and Infrared Video

A Visibility Improvement System for Low Vision Drivers by No...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Hau Ngo Li Tao Ming Zhang A. Livingston V. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

关键词： machine vision Streaming media Charge-coupled image sensors Color Charge coupled devices Infrared imaging Image enhancement Head Vehicles Image restoration

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A multi-view approach on modular PCA for illumination and pose invariant face recognition

A multi-view approach on modular PCA for illumination and po...

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Applied Imagery Pattern Recognition Workshop (AIPR)

作者： P. Sankaran V. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

A modified approach on modular PCA for face recognition is presented in this paper. The proposed changes aim to improve the recognition rates for modular PCA for face images with large variation in light and facial expression. The eyes form one of the most invariant regions on the face. A sub-image from this region is considered. Weight vectors from this region are appended to the existing weight vector for modular PCA. The accuracies for the modified method, the original method and PCA method are evaluated under conditions of varying pose, illumination and expressions using standard face databases.

关键词： Principal component analysis Lighting Face recognition Vectors Image recognition Eyes Facial features Image databases Computational intelligence machine vision

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