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color-image-seg
- 由于彩色图像提供了比灰度图像更为丰富的信息, 因此彩色图像处理正受到人们越来越多的关注。彩色图像分割是彩色图像处理的重要问题, 彩色图像分割可以看成是灰度图像分割技术在各种颜色空间上的应用, 为了使该领域的研究人员对当前各种彩色图像分割方法有较全面的了解, 因此对各种彩色图像分割方法进行了系统论述, 即先对各种颜色空间进行简单介绍, 然后对直方图阈值法、特征空间聚类、基于区域的方法、边缘检测、模糊方法、神经元网络、基于物理模型方法等主要的彩色图像分割技术进行综述, 并比较了它们的优缺点, 通过比
EnclosingRect
- 输入二值图像,可以测出图像中前景元素的大小。有三种测量方式,分别是最小包络矩形、标准(水平)包络矩形和给定方向包络矩形。基于opencv。-Input binary image, the image can be measured in the size of foreground elements. There are three measurement methods, namely, the smallest rectangular envelope, standard (horizont
prospect-of-extracting-images
- 提取图像的前景,就算前景有噪声也能提取出来,有完整的图片演示,易懂!-The prospect of extracting images, even if the prospect of noise can also be extracted, a complete picture presentation, easy to understand!
compressd-sensing
- 压缩感知的发展与应用,这是目前比较热门的研究方向,在医学,图像等领域应用前景广阔。Development and application of compressed sensing-Development and application of compressed sensing, which is the more popular research in medicine, image and other promising areas of application. Development
cxc
- 在源信号和传输信道未知情况下,只利用接收天线的观测数据抽取源信号,称为盲信号分离.盲信号分离不仅是信号处理界、而且也是神经网络界的研究热点课题,在无线数据通信、雷达、图像、语音、医学以及地震信号处理等领域都具有广阔的应用前景.采用自然梯度法和分阶段学习法。-The source signal and transmission channel is unknown circumstances, using only observational data extraction receiving a
segmentation-codebook
- Real-time foreground–background segmentation using codebook model 了解码书进行图像处理(背景与前景)的原理,可以从该文章中获得有益的参考价值-Real-time foreground–background segmentation using codebook model A practical paper for knowing of image processing theory(about foregro
yuzhihuafenge
- 图像分割是把图像划分成具有实际意义的互补交迭的区域的集合。在图像分割之前,图像区域的数目未知,而在分割后各个区域同时满足均匀性和连通性的条件,故图像分割是一个复杂的过程,目前大多数研究都是针对某一类型图像或者某一具体应用的分割。图像阈值化分割的基本思想是确定一个阈值,然后把每个像素点的像素值和阈值相比较,根据比较的结果把像素划分为两类,前景(1)或背景(0)。该方法的关键是确定一个最优的阈值。常用的阈值确定方法有直接门限法、类间最大方差法(otsu法)、分水岭算法、最小误差法、最大熵法等。该段代
MovingDetect
- 利用帧差法从背景图像中提前前景图像的一种经典算法-Frame-difference method using the background image from the foreground image in advance of a classical algorithm
MovingDetect_frame_diff
- 利用帧差法从背景图像中提前前景图像的一种经典算法-Frame-difference method using the background image from the foreground image in advance of a classical algorithm
85520291DecodeFileDemoSource
- 图像处理,包括视频检测,前景目标提取以及背景提取和更新,可以实现目标识别-Image processing, including video detection, foreground object extraction and background extraction and updating, target identification can be achieved
Code
- 用差分法对前景图像突出显示,本程序运用的是codebook方法检测背景的-foreground detection
TransBmpDemo
- VC++显示透明位图,在实际图像显示中常需要将图像某区域设置为透明色,该程序介绍前景位图中介绍如何设置椭圆和矩形区域为透明区域。-VC++ showed clear bitmap, in the actual image display in certain areas will need image set to transparent color, this program introduces prospects bitmap introduces how to set the ellip
bianmajishu
- 图像压缩编码技术的发展历程及前景 图像压缩编码技术的发展历程及前景-Image compression coding technology development process and prospects
4Dview
- 一个三维医学图像实时可视化系统,4DView能有效地解决三维医学图像可视化及其交互操作实时性不强的问题,在临床诊断、治疗和医学研究等领域中具有极大的应用前景.-4D data exploration,This is an extension of the 3 linked cross-sections of a volumic data to the time domain. It is invoked command-line through a syntax as simple as fn
tuxiangfengesuanfasheji
- 图像处理与图像分割,本实验算法较好的实现了目标的前景背景分割。-photo process and division V. Vezhnevets and V. Konouchine. GrowCut: Interactive multi-label ND image segmentation by cellular automata. Proc. of Graphicon
Mark-a-watershed-segmentation
- 分五个部分讲解:1.计算分割函数。图像中较暗的区域是要分割的对象。 2.计算前景标志。这些是每个对象内部连接的斑点像素。 3.计算背景标志。这些是不属于任何对象的像素。 4.修改分割函数,使其仅在前景和后景标记位置有极小值。 5.对修改后的分割函数做分水岭变换计算。-Divided into five sections explain: (1) Calculate the partition function. The dark areas in the image is the
object_find
- 实现对运动目标的跟踪和搜索,在输出图像里面绘出前景图像。-Moving target tracking and search in the output image which draw the foreground image.
FG
- 交互式支持向量机图像分割程序,通过鼠标选取区域实现前景和背景选取-Interactive support vector machine image segmentation procedures, through the mouse to select regions of foreground and background selection
helloopencv
- 摄像头采集视频,分割出背景和前景,背景为灰色,前景为黑白2值图像-get the video from the webcam
Kmeans
- 一种基于K均值聚类的彩色图像颜色增强方法,输入已知前景部分RGB值,代码将根据设定值对输入图像进行重新聚类,并进行灰度图像颜色增强,以利于后续二值化处理-K-means clustering-based color image color enhancement method, enter the known foreground RGB values , the code will re-clustering of the input image according