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dip2
- 基于信息融合的图像边缘检测方法研究,⑴直方图均衡化（histogram equalization），⑵直方图匹配（histogram matching），⑶邻域平均（neighborhood averaging），⑷局域增强（local enhancement）， ⑸中值滤波（median filtering）。-Edge detection method, 1 histogram equalization (histogram equalization). 2 histogram matchi
234
- 本设计是针对第二题采用了两种算法用来识别各种水果。第一种算法是质心法，第二种方法是相关匹配法。 质心法 一．算法思想 质心法的优点在于图像经过任何旋转后，图像边缘到质心的距离求和始终为一个固定值，这样利用这一个特性，就可以辨识出各个图像。 -This design is the second title for the two algorithms used to identify a variety of fruits. The first is a qualitative-f
code
- 基于matlab的虹膜边缘识别 包括边缘检测，归一化，用汉明矩进行特征匹配-Matlab on the edge of iris recognition, including edge detection, normalization, with Hamming moments feature matching
TX_TD_PP_CORR2
- 基于边缘梯度的图像匹配，实现对寻找块图像的精确寻找-Gradient based edge image matching, to achieve the exact image of the search block to find
edge1
- 边缘特征的匹配算法改进研究一篇不错的论文-Edge Feature Matching Algorithm of a good paper
mobanpipeifa
- 模板匹配法，与梯度和Laplacian算子相比较，除了能增强图像边缘外，还具有平滑噪声的优点。-Template matching method, gradient and Laplacian operator with the comparison, in addition to enhance the image edge, but also has the advantages of smoothing the noise.
sfr2
- 用于计算倾斜边缘的MTF的程序，图像源必须是黑白边缘，此方法在低频处的MTF值与理想值基本匹配。-Used to calculate the edge of the tilt MTF program, image source must be black and white edge, this method in the lower frequency area of MTF value and ideal value basic matching.
Hungarian-Algorithm.
- 函数查找最小边的权重匹配给出的M×N的边缘 使用匈牙利算法权重矩阵的权重 A function for finding a minimum edge weight matching given a MxN Edge weight matrix WEIGHTS using the Hungarian Algorithm. - A function for finding a minimum edge weight matching given a MxN Edge we
SIFT
- sift算法实现与研究，包括gaussian，DOG尺度空间的构造，极值点的检测，边缘检测，计算方向，形成描述子，关键点的匹配-sift algorithm and Research
IDAc
- 基于边缘的模板匹配,很重要，匹配很好的,能计算结果，有帮助的-SIFT descr iptor matching，it s very important, and very useful
基于MATLAB的肤色分割和匹配的人脸识别研究
- 对人脸识别的基本进程进行综述,介绍了空间转换及识别的方法；采用低通滤波处理策略,在总结和分析这些处理方法的基础上,运用填孔处理和边缘检测的人脸识别方法进行人脸识别工作；将几种边缘检测算法与人脸识别相结合进行检测,其识别率有可观的提升。(The basic process of face recognition is reviewed, and the method of space conversion and recognition is introduced. On the basis of