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Fpga-based System For Real-time Video Texture Analysis

机译:基于Fpga的实时视频纹理分析系统

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摘要

This paper describes a novel system for real-time video texture analysis. The system utilizes hardware to extract second-order statistical features from video frames. These features are based on the Gray Level Co-occurrence Matrix (GLCM) and describe the textural content of the video frames. They can be used in a variety of video analysis and pattern recognition applications, such as remote sensing, industrial and medical. The hardware is implemented on a Virtex-XCV2000E-6 FPGA programmed in VHDL. It is based on an architecture that exploits the symmetry and the sparseness of the GLCM and calculates the features using integer and fixed point arithmetic. Moreover, it integrates an efficient algorithm for fast and accurate logarithm approximation, required in feature calculations. The software handles the video frame transfers from/to the hardware and executes only complementary floating point operations. The performance of the proposed system was experimentally evaluated using standard test video clips. The system was implemented and tested and its performance reached 133 and 532 fps for the analysis of CIF and QCIF video frames respectively. Compared to the state of the art GLCM feature extraction systems, the proposed system provides more efficient use of the memory bandwidth and the FPGA resources, in addition to higher processing throughput, that results in real time operation. Furthermore, its fundamental units can be used inrnany hardware application that requires sparse matrix representation or accurate and efficient logarithm estimation.
机译:本文介绍了一种新颖的实时视频纹理分析系统。该系统利用硬件从视频帧中提取二阶统计特征。这些功能基于灰度共生矩阵(GLCM),并描述了视频帧的纹理内容。它们可用于各种视频分析和模式识别应用,例如遥感,工业和医疗。硬件在以VHDL编程的Virtex-XCV2000E-6 FPGA上实现。它基于利用GLCM的对称性和稀疏性并使用整数和定点算法计算特征的体系结构。而且,它集成了有效的算法,可快速准确地进行特征计算中的对数逼近。该软件处理从/到硬件的视频帧传输,并且仅执行互补的浮点运算。使用标准测试视频剪辑对所提出系统的性能进行了实验评估。该系统已实现并经过测试,其性能分别达到CIF和QCIF视频帧分析的133和532 fps。与最先进的GLCM特征提取系统相比,除了更高的处理吞吐量之外,所提出的系统还更有效地利用了存储器带宽和FPGA资源,从而实现了实时操作。此外,其基本单位可用于任何需要稀疏矩阵表示或准确有效的对数估计的硬件应用中。

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