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Here are described some methods of image and video segmentation.
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利用VC++实现图像处理,主要是对图像进行图像分割处理。-Using vc++ realize image processing, is mainly to the image segmentation.
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The colors features based on overall histogram
neglecting images’ spacial information may be imprecise
in image retrieval, since different image may has same
histogram. Two color features with special information
based on image fixed segmenta
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brain image segmentation and registration
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1.首先单击载入图像菜单项(载入车辆图像),图像在images文件夹下面。
2.然后单击车牌定位与识别单项,依次进行车牌提取、倾斜校正、字符分割、字符识别。
注:本程序使用的是OpenCV2.1版本,在没有安装此版本软件的机器上运行时需要将cv210.dll,cvaux210.dll,cvcore210.dll,highgui210.dll,ml210.dll这五个文件拷贝至*.exe可执行文件下。-First click Load Images menu items (lo
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cbirIn this paper, we present a new framework for effective content-based image retrieval (CBIR) using rectangular segmentation. In image segmentation, speed is more important than accuracy in CBIR. We propose a new rectangular approximate image segm
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图像处理程序,包含图像降噪,图像增强,图像分割等-Image processing procedures, including image noise reduction, image enhancement, image segmentation, etc.
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对复杂图象进行基于颜色的聚类分割、轮廓提取、种子填充、边缘检测基本算子等-Complex clustering-based color image segmentation, contour extraction, seed filling, edge detection operator and other basic
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车牌定位系统代码。车牌自动识别是计算机视觉、图像处理与模式识别技术在智能交通领域应用的一项重要研究课题,是实现交通管理智能化的关键环节。而车牌定位则是车牌自动识别系统的关键技术之一,也是其难点之一。车牌定位系统对车牌识别系统来说至关重要,其定位准确度在很大程度上影响着以后的字符分割和识别结果。因此,汽车图像中牌照的正确定位是车牌识别技术中的关键所在。目前,主要通过两条技术路线进行车牌定位的研究。早期,由于受到计算机运算速度和内存大小的影响,考虑到实时性,车牌定位主要是基于灰度图像处理技术。近年来
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GMM for image segmentation
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Simple GMM os image segmentation
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This folder contains the code foR Image Segmentation
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