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屋顶边缘
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  roof edge
     Segmentation of Fingerprint Images Based on Multi-Scales Roof Edge Detection
     基于多尺度屋顶边缘检测的指纹图象分割方法
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     According the characteristic of computer vision measurement, the author researched the methods of color image converting to gray and presented judging rules of gray transform arithmetic. The judging functions of keeping the edge structure characteristic have been presented aiming to step edge and roof edge.
     针对视觉测量的特点,研究彩色图像灰度化方法,提出了彩色图像灰度化效果好坏的评判标准,给出了阶跃边缘、屋顶边缘保持边缘结构特征的评价函数。
短句来源
     The ridges and valleys are considered as roof edge and their two sides are taken for step edges, then ridges and valleys can be located based on roof edge detection of multi scales B spline wavelet, and the area of the ridges and valleys is decided by the step edges.
     该方法是将上述脊和谷看成是屋顶边缘 ,脊和谷的两个边界看成是阶跃边缘 ,并利用基于 B样条小波的多尺度屋顶边缘检测方法来实现脊和谷的分割 ;
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  相似匹配句对
     Edge
     边缘
短句来源
     Experiencing the Edge
     感受边缘
短句来源
     sempervivum fecforum
     屋顶长生花
短句来源
     Segmentation of Fingerprint Images Based on Multi-Scales Roof Edge Detection
     基于多尺度屋顶边缘检测的指纹图象分割方法
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     Primary School——On the Roof
     屋顶小学(英文)
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  roof edge
Detectors have been constructed for five features, namely, step edge (five parameters), roof edge (five parameters), line (six parameters), corner (five parameters), and circular disc (six parameters).
      
A typical example for this is a building roof edge, which is usually exactly above an edge between the wall of the building and the ground.
      
In both normal and retroverted conditions the mouth opening spirals gradually into increasing anteversion distal to the roof edge.
      
Like the other test methods, this one uses no wind and does not deal with the roof edge.
      
Position 1 is located in the middle between sliding roof and roof edge and must be regarded as reference position only.
      
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A new method to locate and segment human faces in a complex background is proposed. This system utilizes a hierarchical knowledge based method and consists of three levels. The higher two levels are based on detecting maximum(corresponding to faces) and minimum(corresponding to eyes) in multiresolution image using B spline dyadic wavelet transform, and then initial selection is made using some knowledge, e.g. the relation of scale between eyes and face,symmetry of face, etc. The last level will make the face...

A new method to locate and segment human faces in a complex background is proposed. This system utilizes a hierarchical knowledge based method and consists of three levels. The higher two levels are based on detecting maximum(corresponding to faces) and minimum(corresponding to eyes) in multiresolution image using B spline dyadic wavelet transform, and then initial selection is made using some knowledge, e.g. the relation of scale between eyes and face,symmetry of face, etc. The last level will make the face and eyes certainly according to the features of face. This method can locate and segment unknown human faces spanning a wide range of sizes in an intensity image. Some experimental results are presented.

提出了一种新的在复杂背景下对未知大小、位置和数目的人脸进行定位和分割的算法.它利用基于知识的金字塔方法,主要由3部分组成:较高的2级是在多尺度屋顶边缘检测的基础上,先利用B-样条二进小波变换来检测在不同分辨率下的极小值点(对应眼睛)和极大值点(对应人脸);再利用尺度、包含和对称等关系进行初步筛选;最后利用人眼的特征确定眼睛的位置.因此,这种方法能够在复杂背景的灰度图像中检测不同尺度下的未知人脸,并进行初步的分割.最后,给出了一些实验结果.

In this paper, based on wavelet transform, we propose a new method of multiscale ridge betection in an image, and then the formulas, which are for computing maximal curvature and its direction in there, is derived. Combined with face feature, this method is used for detecting and segmenting faces and its feature (eyesetc.) in complex background. The effectiveness of the new method is confirmed by the experiment in the end ofthis paper.

本文利用小波为工具提出了在多尺度检测图象中屋顶边缘的方法,导出了该处屋顶边缘的最大曲率及其方向的计算公式;并将其结合人脸的特点用以在较复杂背景的图象中确定人脸及其器官(如眼睛)的位置和进行初步的分割,此方法在实验中取得了良好的效果。

Automatic fingerprint identification is one of the most significant biometrics technology. Preprocessing of fingerprint image play an important role in automatic fingerprint identification system(AFIS) and segmenting the ridges and valleys from fingerprint images is the basic task of preprocessing. This paper presents a new segment method for the ridges and valleys of fingerprint images. The ridges and valleys are considered as roof edge and their two sides are taken for step edges, then ridges and valleys can...

Automatic fingerprint identification is one of the most significant biometrics technology. Preprocessing of fingerprint image play an important role in automatic fingerprint identification system(AFIS) and segmenting the ridges and valleys from fingerprint images is the basic task of preprocessing. This paper presents a new segment method for the ridges and valleys of fingerprint images. The ridges and valleys are considered as roof edge and their two sides are taken for step edges, then ridges and valleys can be located based on roof edge detection of multi scales B spline wavelet, and the area of the ridges and valleys is decided by the step edges. The valid scale range for roof target detection is discussed in detail, and we also give the simply and concretely segment method. The effectiveness of this algorithm has been testified for different quality fingerprints images. It must be point out that this segment method can be applied to detection of other similar roof targets.

针对指纹图象的细节识别问题 ,提出了一种新的分割指纹图象中脊和谷的方法 .该方法是将上述脊和谷看成是屋顶边缘 ,脊和谷的两个边界看成是阶跃边缘 ,并利用基于 B样条小波的多尺度屋顶边缘检测方法来实现脊和谷的分割 ;同时详细讨论了精确确定屋顶状目标所需的尺度范围 ,并给出了检测目标的具体方法 .实验证明 ,该方法用于不同质量的指纹图象的检测都取得了令人满意的效果 .需要指出的是 ,该方法也同样适用于其它类似屋顶状目标的检测 .

 
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