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shape the ri new - Fourier transform descr iptor-shape the ri new- Fourier transform descr iptor
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Solutions to problems in the field of digital image processing generally require extensive experimental work involving software simulation and testing with large sets of sample images.
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傅立叶描述子,用来实现对边缘图像的检测和使用傅立叶描述子进行重现-Fourier descr iptor is used to achieve on the edge of the image detection and the use of Fourier descr iptors to reproduce
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基于极坐标和傅里叶描描述子的二值商标图像检索
-Binary Trademark Image Retrieval based on polar coordinates and Fourier descr iption descr iptor
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傅立叶描述子的详细文文档,用于物体形状识别
-Fourier descr iptor text documents, and for object shape recognition
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fourierDescr iptor.rar, 抽取目标图形的轮廓及其fourier Descr iptor算子, 然后对此fourier descr iptor进行标准化(normalized), 标准化以后的算子满足orientation,scale 和translation invariant。 再将此算子与某标准图形的fourier 算子进行比较, 若各项差的平方小雨某范围,则断定与此标准图像类似。
-fourierDescr iptor.rar extract the targe
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skin segmentation: recognizing skin part in RGB space, extract the skin part and using Fourier descr iptor to reconstruct the margin
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Fourier descr iptor which is invariant to rotation and scaling
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fast快速角点检测算法以及角点检测与傅立叶描述子-fast corner detector and fourier descr iptor
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Fourier descr iptor example on different shapes.Can reconstruct shape with few coeffecients
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fourier descr iptor of figures
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lle在图像检索中的应用,GUI界面,包括提取HSV颜色空间的颜色矩特征的子程序,提取图像 不变矩的子程序,提取图像文理特征的子程序,基于傅立叶描述子的纹理特征提取子程序等。-Lle application in image retri , the GUI interface, including extraction of HSV color space the color of the torque characteristics of a subroutine, extract the i
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compute the fourier descr iptor of a curve
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基于叶片数字图像的植物识别是自动植物分类研究的热点。但是随着植物种类的增加,传统的分类方法由 于提取的特征比较单一或者分类器结构过于简单,导致叶片识别率较低。为此,本文提出使用纹理特征结合形状 特征进行识别,并且使用深度信念网络构架作为分类器。纹理特征通过局部二值模式、Gabor 滤波和灰度共生矩阵 方法得到。而形状特征向量由 Hu 氏不变量和傅里叶描述子组成。为了避免过拟合现象,使用“dropout”方法训练 深度信念网络。这种基于多特征融合的深度信念网络的植物识别方法-Plant based
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傅里叶描述子用于图像特征提取,对图像缩放,平移和旋转具有转换不变性,适合形状特征的提取(The Fourier descr iptor is used for image feature extraction, the image zooming, translation and rotation are invariant and suitable for the extraction of shape features.)
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