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Abstract: Effective data processing is required with the fast development of multimedia technology. Compressed-domain images/video processing techniques have captured the attention of many researchers in recent years, and research on face detection a
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车牌识别C++Builder代码，首先要把车牌图像灰度化，接着对图像进行中值滤波进行初步降噪，下一步进行Sobel纵向边缘检测，即增强车牌纵向边缘，边缘检测后进行二值化处理，此时车牌区域特征得到进一步加强，但同时又加强了背景中的部分噪声，所以再对其腐蚀，然后定位及截取车牌，最后对车牌进行二值化。
-LPR C Builder code, first and foremost, we should plates gray, Then the image median filtering for
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这是一个在复杂背景下，对目标圆孔的检测，但是它的背景相对比较特殊-This is a complex background, the right of the hole target detection, but its relatively unique background
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基于openCV的手势检测与识别代码，其中使用了基于颜色的分割算法，如果结合运动检测和减背景方法，算法将会更加稳健。-Hand gesture detection and recognition using openCV and the color based segmentation method. If, combinned with motion detection and background substraction, it supposes to be robuster.
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视频跟踪检测 背景核密度估计建模，欢迎指正，-Detection of the background video track modeling kernel density estimation, please correct me, thank you
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边缘提取算法提取细胞轮廓 适用于前景背景反差巨大-An object can be easily detected in an image if the object has sufficient
contrast from the background. We use edge detection and basic morphology
tools to detect a prostate cancer cell.
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视频帧分析源码，用于车辆检测及车牌识别，采用背景差分法-Analysis of source video frame for vehicle license plate detection and identification, using the background difference method
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采用非参数背景建模，MFC，对运动目标进行检测，有很高的参考价值-Using non-parametric background modeling, MFC, the moving target detection, a high reference value
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这个程序是对一段avi视频进行人脸检测，要求背景比较简单，因为把膨胀腐蚀的部分去掉了，所以实时性还不错，下面的图片是取的其中的某一帧。-This program is a avi video face detection, required background is relatively simple, because the expansion of some corrosion removed, so time was good, the following picture is take
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大名鼎鼎的方帅的博士学位论文---目前,计算机智能视频监控在理论和应用上都面临着很多难题,国内外大批学者投身于该领域的研究和探索,并且取得了大量的成果.本文是在这些成果的基础上,对计算机智能视频监控系统的关键技术进行研究.主要贡献可概括如下:首先,对目标检测技术进行了研究,并提出了一种基于背景建模的运动目标检测算法.利用统计的方法建立了基于颜色和颜色梯度的背景模型,并实时地对背景模型进行更新,最后将这两种背景模型综合考虑对目标进行了有效的检测.接着,研究了复杂背景下多目标跟踪问题,提出了基于蒙特
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这篇论文提出了一种新的为实现车辆检测和跟踪的自适应背景提取和更新算法-This paper proposes a new adaptive background extraction and updating algorithm for vehicle detection
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人脸表情识别是模式识别领域中一个重要的研究方向。人脸表情识别包括：从背景图像中检测人脸、图像采集、对人脸图像进行预处理、PCA提取表情特征、表情识别。-Face recognition is an important research direction in the field of pattern recognition. Face recognition is made up of the following parts: face detection from the backgrou
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此代码用于运动目标检测，尤其是前期的目标背景建模等具有较好的效果-This code is used for moving target detection, especially early in the target background has a good effect modeling
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基于背景差分法的是视频运动目标检测，该算法包含背景差分核心算法以及滤波处理阴影处理等后续图像处理-Background subtraction is based on video motion detection, background subtraction of the algorithm contains the core algorithm and the filtering processing, the shadow of the follow-up image processing
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很简单的人脸识别程序，要求图片背景比较单一，识别效果一般，供初学者学习参考-Face recognition process is very simple, requiring relatively simple image background, identify the general effect, for beginners to learn information
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这个程序是对一段avi视频进行人脸检测，要求背景比较简单，因为把膨胀腐蚀的部分去掉了，所以实时性还不错，下面的图片是取的其中的某一帧。-This program is a avi video, face detection, requires relatively simple background, as part of the expansion of corrosion removed, so real time is also good, the following picture is
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基于肤色的人脸检测，要求背景比较简单，下面的图片是取的其中的某一帧-Face detection based on skin color, requiring relatively simple background, the following picture is taken in which a frame
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视频帧分析源码，用于车辆检测及车车牌识别，采用背景差分法可直接使用。-Analysis of source video frame for vehicle license plate detection and recognitionn, the background difference method using the full source code can be used directly.
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本文选用了背景减法、帧间差分法和光流法。背景减法是通过将当前帧与背景帧相减得出灰度差值并将此差值与阈值比较判断是否有运动目标。-This paper chose the background subtraction and frame difference method and optical flow method.Background subtraction is through to the current frame and background frame subtraction gr
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使用bp神经网络算法来进行车辆的识别检测，通过使用该方法，可以在简单背景下检测出运动的车辆-Use bp neural network algorithm to detect vehicle identification, by using this method, the motion of the vehicle can be detected in a simple background
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