| 1. | The application of gabor filter in fingerprint segmentation
滤波器在指纹图像分割中的应用 |
| 2. | The principle of gabor filter is expounded
阐述了gabor滤波器原理。 |
| 3. | ( 4 ) a fingerprint image enhancement method based on gabor filter is presented and realized
( 4 )给出并实现了一种基于gabor滤波的指纹图象增强改进方法。 |
| 4. | The neural network recognizing algorithm based on multi channel gabor filter feature is presented
相应地给出了一个基于多通道gabor滤波器特征神经网络识别算法。 |
| 5. | The multi channel gabor filter is designed based on theory and practicality , the texture features of gray image target are extracted
根据理论分析和实际需要，设计了多通道gabor滤波器，提取了灰度图像目标纹理特征。 |
| 6. | Different fonts are regarded as different textures , then font is identified through texture analysis with multi - channel gabor filters
将不同字体的文本看作不同的纹理，使用多通道gabor滤波器的纹理分析方法识别字体。 |
| 7. | In gabor filter , we use eight directional filtering to process fingerprint image to compare wiener filtering , we get good process result
在预处理中,采用八个方向的gabor滤波对指纹图像进行滤波,把它与维纳滤波作比较,得了较好的试验结果。 |
| 8. | The gabor filter is used to extract the characteristics . in this method , the jet which is a kind of the multi - scaled analysis methods is used , and get a good result
本文使用gabor滤波器，多尺度提取方向特征，在对方向性强的纹理特征的分割中有很好的效果。 |
| 9. | By comparison among the results when using a lot of algorithms in feature extraction , we choose gabor filter for its good quality in low frequency
通过对多种算法进行比较，本文选择了使用gabor滤波作为提取纹理的特征的方法。在特征分类算法中，本文选择简单的聚类算法。 |
| 10. | The improvements make segmentation more effective . in image enhancement , the paper improves the algorithm of fingerprint image enhancement based on gabor filter according to its disadvantages
改进后的分割算法对对比度不均衡、较复杂噪声的指纹图像均具有满意的分割效果。 |
