文件名称:2
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基于Gabor变换的图像纹理识别。
提出了一种改进的Gabor变换的图像纹理增强算法,将空域的纹理图像变换到联合空间频率域并将联合空间
频率域的能量分布作为掌纹的特征,Gobar滤波器在频域内对子块其主方向上频率能量分布进行滤波,特征向量进行了匹配
识别,增强特征纹线信息并对核心区域进行多方向空间频率能量滤波合成,同时也对滤波算法进行了优化,有效地减少了运
算量。-Gabor transform based image texture recognition. An improved image of the Gabor transform texture enhancement algorithm, the airspace of the texture image transform frequency domain to the joint space and joint space frequency domain characteristics of the energy distribution as a palm, Gobar filter pair in the frequency domain block its the main direction of the energy distribution of the frequency filtering, feature vectors were matched to identify, enhance the features of ridge information as well as the core region of multi-dimensional spatial frequency energy filter synthesis, but also on the filtering algorithm has been optimized, effective in reducing the computational complexity.
提出了一种改进的Gabor变换的图像纹理增强算法,将空域的纹理图像变换到联合空间频率域并将联合空间
频率域的能量分布作为掌纹的特征,Gobar滤波器在频域内对子块其主方向上频率能量分布进行滤波,特征向量进行了匹配
识别,增强特征纹线信息并对核心区域进行多方向空间频率能量滤波合成,同时也对滤波算法进行了优化,有效地减少了运
算量。-Gabor transform based image texture recognition. An improved image of the Gabor transform texture enhancement algorithm, the airspace of the texture image transform frequency domain to the joint space and joint space frequency domain characteristics of the energy distribution as a palm, Gobar filter pair in the frequency domain block its the main direction of the energy distribution of the frequency filtering, feature vectors were matched to identify, enhance the features of ridge information as well as the core region of multi-dimensional spatial frequency energy filter synthesis, but also on the filtering algorithm has been optimized, effective in reducing the computational complexity.
相关搜索: 掌纹
识别
掌纹
palm
gabor
filter
for
texture
feature
能量
matlab
gobar
filter
palmprint
gabor
frequency
domain
图像
能量
image
multi-dimensional
wavelet
segmentation
识别
掌纹
palm
gabor
filter
for
texture
feature
能量
matlab
gobar
filter
palmprint
gabor
frequency
domain
图像
能量
image
multi-dimensional
wavelet
segmentation
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2.kdh