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本项目名称是：基于FPGA的指纹识别模块设计。
主要内容为：本模块采用xilinx公司的Spartan 3E系列XC3S500E
型FPGA作为核心控制芯片，通过富士通公司的MFS300滑动式电容指纹传感器对指纹图象进行提取，然后对提取的指纹图像进行灰度滤波、图像增强、二值化、二值去噪、细化等预处理，得到清晰的指纹图象，再从清晰的指纹图象中提取指纹特征点，存入外部FLASH作为建档模板。指纹比对时，采用同样的方法获得清晰的指纹图像，建立比对模板，然后将比对模板与建档模板利用点模式匹配
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This project deals with the tracking and following of single object in a sequence of frames
and the velocity of the object is determined. Algorithms are developed for improving
the image quality, segmentation, feature extraction and for deterring
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Abstract—This paper proposes a new technique for face detection
and lip feature extraction. A real-time field-programmable
gate array (FPGA) implementation of the two proposed techniques
is also presented. Face detection is based on a naive Bay
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交通信号灯的检测是复杂场景下交通灯识别的重点。采用了色彩分割与关联滤波方案进行交通灯的检测。首先，建立交通信号灯的高斯模型，利用高斯向量与多色彩空间结合的方法进行图像分割。然后，采用基于区域增长与相似性判定的关联滤波，对色彩分割后的图像进行处理。最后，使用基于canny算子的边缘提取算法获取方向指示灯轮廓特征，并使用基于改进hu不变矩和马氏距离对方向指示信号灯进行分类。-The detection of traffic lights is the focus of traffic lights
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该实验报告对指纹识别系统整体的构建进行了说明，其中还包括遇到的问题以及解决过程的分析。对指纹识别系统的总体设计和各部分设计进行了相应说明，首先将整个系统分为三个部分：指纹预处理，特征值提取和指纹特征匹配；其中指纹预处理部分又可分为：指纹图像的分割、均衡、增强、二值化、细化等部分。每部分选择最优化的算法，首先用C语言进行软件实现，然后与硬件相结合，以DSP TMS320VC5416为平台，在DSP集成开发环境CCS上进行算法调试。
-The test reports on fingerprin
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Application of small area variance comparison, simple procedures, For feature extraction, signal de-noising, Achieve a grayscale image and further control for video surveillance.
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For feature extraction, signal de-noising, Using matlab to calculate the Mahalanobis distance for the image, Based on SVPWM three-level inverter matlab simulation.
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Using weighted model nodes in the network strength and weight are power law distribution, Complete set content, basic hyperspectral image processing, Is a good learning materials to learn PCA feature extraction.
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Based on multi-document image obtained combining technique, Matching Pursuit and orthogonal matching pursuit, For feature extraction, signal de-noising.
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The aims to give the students the fundamentals of digital image processing,
covering topics from the following list: image models and physical imaging systems;
visual perception; rendering systems; linear filtering; linear transforms; mathematical
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Including compression ratio, image restoration computing uptime and peak signal to noise ratio, For feature extraction, signal de-noising, Contains two clients receive link-level communications program.
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Complete set content, basic hyperspectral image processing, For feature extraction, signal de-noising, matlab prepared cellular automata.
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