非接触成像方式下手掌特征提取方法研究
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摘要
人的手掌包含丰富的静脉信息和掌纹信息，有研究表明，掌纹的分布具有唯一性和稳定性，可以用来作为身份鉴别的依据。静脉位于皮下，是身体内部特征，具有一定防伪性。基于掌纹和掌静脉的多模态手识别可以提高个人身份鉴别的可靠性，同时，手图像可以通过非接触方式获取，采集方式具有非侵犯性，大众接受程度高，采集方式更加卫生。以上特点使手掌特征识别技术在门禁系统中具有很大优势。
相对接触式成像方式，利用非接触成像方式采集手图像时，手相对成像装置的方向、位置和拍摄距离是不确定的，这导致对于同一个人，每次采集的手图像中手的大小、方向和位置可能不相同。为此，可以有两种解决方案，一是对图像中手进行归一化，从而使手掌特征与手成像造成的平移、旋转和比例缩放无关。一是提取与平移、旋转和比例缩放无关的特征。由于归一化过程改变了原有图像的部分性质，而改变的这部分性质可能影响特征的提取，同时，归一化过程也增加了运行时间。因此，本文选择后一种方案。
本文的主要工作和成果如下：
(1)为了利用手掌静脉和掌纹主线上各点与掌心稳定参考点的空间相对位置构造与手掌旋转、平移和比例缩放无关的特征，提出了一种手掌内切圆定位方法，通过构造一个掌心内切圆来选择掌心稳定的参考点。为了保证内切圆具有唯一性，设计内切圆具备如下条件：分别与手掌两侧轮廓线相切，并通过中指、无名指的指根点。由圆的几何性质可知，圆边界上任意两点的中垂线必经过圆心，且圆的切线必垂直于经过该切点的半径。根据这两条性质，依次分别对位于食指外侧手掌轮廓线上和小手指外侧手掌轮廓线上的手掌边缘点进行扫描，确定内切圆圆心的位置以及内切圆的半径。最后，利用内切圆内图像灰度曲面做差形成的差曲面的标准差来表征内切圆的定位稳定性。将同一手多次采集的手图像得到的多个标准差再次计算标准差，将其作为定位稳定性的评价值。内切圆内图像越相似，定位越稳定，标准差越小。基于自建图像库对定位方法进行验证，本文方法定位稳定性评价值为0.751，平均定位时间为1116ms，传统的内切圆定位方法定位稳定性评价值为0.837，平均定位时间为1555ms。实验结果证明，该方法可以解决手掌定位问题，与传统方法相比，该定位方法更稳定，却需要更少的定位时间。
(2)在手掌内切圆内利用静脉分叉点与内切圆圆心的相对位置构造了一组与手掌旋转，平移，比例缩放无关的手掌特征。首先，利用内切圆内静脉分叉点和内切圆圆心定义相对半径及相邻夹角参数；其次，由相对半径和角度参数建立二维特征向量空间，将静脉分叉点转换成该特征向量空间内的一系列特征点；最后，将特征向量空间中特征点分布结构的相似性作为匹配依据。利用两个方法对所构造特征的有效性进行评价。一方面是特征的稳定性，将手图像做旋转和比例缩放处理，处理后的图像和原图像进行匹配，实验结果表明，手图像的旋转和比例缩放对构造的手掌特征不造成影响。另一方面是特征的唯一性，基于实际环境建立近红外光下的手图像库，对算法性能进行验证。在拇指自然伸开、四指合拢的成像方式下和五指自然伸开的成像方式下，分别得到等误率0.96%和4.91%。结果表明，该方法在手产生比例缩放、旋转和平移后仍可获取较好的识别效果。该方法由于引入基于特征参量空间的匹配方法，具有一定程度的特征点提取容错性，且可通过少量特征获取较好的识别效果，适用于需要较小的特征数据存储空间的脱离计算机的手识别仪器。
(3)在手掌内切圆内利用手掌静脉以及掌纹主线空间分布构造了一组与手掌旋转，平移，比例缩放无关的手掌特征。首先从内切圆圆心做若干条放射状线段相交于圆周，将圆心与中指和无名指指根的连接点连线方向作为参考方向，同时，构造模板计算各特征线段上各点的梯度值，根据各线段上各点的梯度值计算质心相对半径，将其定义为特征参量，以此构成特征向量空间；其次，基于自建的手图像库，对不同模板尺寸下的特征稳定性和不同线段数量下的方法识别性能进行分析，实验结果表明，当选择子模板尺寸为77时，特征线段质心点位置稳定性最好。特征线段的数量为60时，等误率相对稳定，不再显著降低。最后从两个角度对特征的有效性进行验证：1)特征的稳定性。将170幅手图像做旋转和比例缩放处理，利用变换后的手图像和原图像进行匹配，匹配率在97%以上；2)特征的唯一性。在子模板尺寸为77，构造线段数量为60条的前提下，可以获得小于0.4%的等误率，特征提取时间为0.0019秒。实验结果表明，所构造的特征具有平移、旋转和比例缩放不变性，同时，特征提取时间较快，适用于对实时性要求较高的手识别装置。
Person’s palm contains rich palm vein and palmprint.Study has shown that thedistribution of palmprint is unique and stable.It can be used as the basis for authentication.Palm vein is the internal body characteristics, which has certain anti-falsification.Multi-modal palm recognition based on palmprint and palm vein can improve thereliability of the personal authentication. At the same time, the palm image can be acquiredby contactless acquisition mode, which is more hygienic and be adopted easily by peoplebecause of its non-intrusive.The above features make palm identification technology has agreat advantage in the access control system.
Contrast to the contact acquisition mode, the direction, position and shooting distancebetween the palm and the imaging device is uncertain when collecting palm image withcontactless acquisition mode. There are two solutions. One is to normalize the palm image.Another is to extract the translation, rotation and scaling invariant hand feature. Thenormalization changes some properties of the original image that may affect the featureextraction. At the same time, the normalization process also increases the running time. Sothis thesis chooses the latter program.
Main works and results of this thesis are as follows.
(1) In order to select the stable reference point of palm, a palm localization methodbased on inscribed circle is proposed in this thesis. It chooses the circle center as the palmreference point. In order to ensure the inscribed circle is unique, the inscribed circle isdesigned to meet the following criterion: the inscribed circle is tangent to both side of thepalm contour and through the junction point of middle finger and ring finger. By thesymmetry of the circle, the perpendicular bisector that through any two points on theboundary will pass through the circle center and the tangent will be perpendicular to theradius that pass through the tangent point. According to these natures, this methoddetermines the centres and radiuses of inscribes circle by detecting a boundary point in the palm contour lines of the lateral index finger and lateral pinkie outside respectively. Finally,it judges the positioning stability by the standard deviation of gray difference surfacewithin inscribes circle. The more similar the image within inscribes circle, the higher thepositioning stability, and the smaller the standard deviation. The positioning method isverified based on self-build image database.The positioning stability of the proposedmethod is0.751and the average localization time is1116ms. The positioning stability oftraditional inscribes circle positioning method is0.837and the average localization timeis1555ms. Experimental results demonstrate that the proposed method can sresolve theproblem of palm positioning.Compared with traditional methods, the proposed method hashigher positioning accuracy but it need fewer localization time.
(2) In this thesis, the relative positions of the vein crossover points and the inscribecircle center are constructed into a set rotation, translation, scaling invariant features.Firstly, the inscribed circle of palm is obtained. The relative radius and relative angle isdefined by the use of the intersection point inside circle and the circle center. Then, thetwo-dimensional feature vector space is established by the radius and angle parameters.And image is converted to a series of feature points in the feature space. Finally, similarityof the distribution structure of feature points in the feature vector space is taken as thematching basis. Use two methods to evaluate the effectiveness of the features. On the onehand, it is to analyze the stability of the features by match the original image and the imageafter rotation and scaling. Experimental results show that the rotation and scaling have noimpact on the constructed palm features. On the other hand, it is to analyze the uniquenessof the features. The performance of the proposed method is verified by self-build imagedatabase.When thumb naturally stretch and four fingers close, the equal error rate(EER) is0.96%.When five fingers naturally stretch, the equal error rate(EER) is4.91%.Experimental results show that the method can obtain good recognition effect. It hasinvariant to scaling, rotation and translation and fault tolerance of feature pointextraction.This method is suitable for palm identification instruments that need smallerdata storage space, because it can obtain better recognition results by a small number offeatures.
(3) This thesis proposes a novel feature extraction method which can reflects thegeometric features of palmprint and palm vein without being affected by the scaling,rotation and translation. Firstly, several radiation segments are made between the inscribedcircle center and circumference. The reference direction is the direction of the circle center with the junction point of middle finger and ring finger. Meanwhile, the gradient value ofpixels in the feature line segment is calculated by creating template. The feature vectorspace is established by the relative radius of feature line segment’s centroids. Secondly, thepalm image database is established based on the practical application environment. Thefeature stability in different size of sub-template and recognition performance in differentnumber of feature line segments is analyzed. When the size of sub-template is7×7, thefeature stability is the best.When the number of feature line is sixty, the recognitionperformance is relatively stable and not any more significantly increased.Finally, use twomethods to evaluate the effectiveness of the features.1) The stability of the features.Onehundred and seventy hand images is rotated and scaled.The matching rate which theoriginal image and transformed images is greater than97%;2) The uniqueness of thefeatures.When the size of sub-template is equal to seven and the number of feature linesegments is sixty, the equal error rate(EER) is less than0.4%and feature extraction time is0.0019s. The experimental results show that the method can extract out stablecharacteristics whenever the hand image is scaled, rotated or translated. And computingspeed is faster.This method is suitable for palm identification device which has higherrequirements for real-time.
相对接触式成像方式，利用非接触成像方式采集手图像时，手相对成像装置的方向、位置和拍摄距离是不确定的，这导致对于同一个人，每次采集的手图像中手的大小、方向和位置可能不相同。为此，可以有两种解决方案，一是对图像中手进行归一化，从而使手掌特征与手成像造成的平移、旋转和比例缩放无关。一是提取与平移、旋转和比例缩放无关的特征。由于归一化过程改变了原有图像的部分性质，而改变的这部分性质可能影响特征的提取，同时，归一化过程也增加了运行时间。因此，本文选择后一种方案。
本文的主要工作和成果如下：
(1)为了利用手掌静脉和掌纹主线上各点与掌心稳定参考点的空间相对位置构造与手掌旋转、平移和比例缩放无关的特征，提出了一种手掌内切圆定位方法，通过构造一个掌心内切圆来选择掌心稳定的参考点。为了保证内切圆具有唯一性，设计内切圆具备如下条件：分别与手掌两侧轮廓线相切，并通过中指、无名指的指根点。由圆的几何性质可知，圆边界上任意两点的中垂线必经过圆心，且圆的切线必垂直于经过该切点的半径。根据这两条性质，依次分别对位于食指外侧手掌轮廓线上和小手指外侧手掌轮廓线上的手掌边缘点进行扫描，确定内切圆圆心的位置以及内切圆的半径。最后，利用内切圆内图像灰度曲面做差形成的差曲面的标准差来表征内切圆的定位稳定性。将同一手多次采集的手图像得到的多个标准差再次计算标准差，将其作为定位稳定性的评价值。内切圆内图像越相似，定位越稳定，标准差越小。基于自建图像库对定位方法进行验证，本文方法定位稳定性评价值为0.751，平均定位时间为1116ms，传统的内切圆定位方法定位稳定性评价值为0.837，平均定位时间为1555ms。实验结果证明，该方法可以解决手掌定位问题，与传统方法相比，该定位方法更稳定，却需要更少的定位时间。
(2)在手掌内切圆内利用静脉分叉点与内切圆圆心的相对位置构造了一组与手掌旋转，平移，比例缩放无关的手掌特征。首先，利用内切圆内静脉分叉点和内切圆圆心定义相对半径及相邻夹角参数；其次，由相对半径和角度参数建立二维特征向量空间，将静脉分叉点转换成该特征向量空间内的一系列特征点；最后，将特征向量空间中特征点分布结构的相似性作为匹配依据。利用两个方法对所构造特征的有效性进行评价。一方面是特征的稳定性，将手图像做旋转和比例缩放处理，处理后的图像和原图像进行匹配，实验结果表明，手图像的旋转和比例缩放对构造的手掌特征不造成影响。另一方面是特征的唯一性，基于实际环境建立近红外光下的手图像库，对算法性能进行验证。在拇指自然伸开、四指合拢的成像方式下和五指自然伸开的成像方式下，分别得到等误率0.96%和4.91%。结果表明，该方法在手产生比例缩放、旋转和平移后仍可获取较好的识别效果。该方法由于引入基于特征参量空间的匹配方法，具有一定程度的特征点提取容错性，且可通过少量特征获取较好的识别效果，适用于需要较小的特征数据存储空间的脱离计算机的手识别仪器。
(3)在手掌内切圆内利用手掌静脉以及掌纹主线空间分布构造了一组与手掌旋转，平移，比例缩放无关的手掌特征。首先从内切圆圆心做若干条放射状线段相交于圆周，将圆心与中指和无名指指根的连接点连线方向作为参考方向，同时，构造模板计算各特征线段上各点的梯度值，根据各线段上各点的梯度值计算质心相对半径，将其定义为特征参量，以此构成特征向量空间；其次，基于自建的手图像库，对不同模板尺寸下的特征稳定性和不同线段数量下的方法识别性能进行分析，实验结果表明，当选择子模板尺寸为77时，特征线段质心点位置稳定性最好。特征线段的数量为60时，等误率相对稳定，不再显著降低。最后从两个角度对特征的有效性进行验证：1)特征的稳定性。将170幅手图像做旋转和比例缩放处理，利用变换后的手图像和原图像进行匹配，匹配率在97%以上；2)特征的唯一性。在子模板尺寸为77，构造线段数量为60条的前提下，可以获得小于0.4%的等误率，特征提取时间为0.0019秒。实验结果表明，所构造的特征具有平移、旋转和比例缩放不变性，同时，特征提取时间较快，适用于对实时性要求较高的手识别装置。
Person’s palm contains rich palm vein and palmprint.Study has shown that thedistribution of palmprint is unique and stable.It can be used as the basis for authentication.Palm vein is the internal body characteristics, which has certain anti-falsification.Multi-modal palm recognition based on palmprint and palm vein can improve thereliability of the personal authentication. At the same time, the palm image can be acquiredby contactless acquisition mode, which is more hygienic and be adopted easily by peoplebecause of its non-intrusive.The above features make palm identification technology has agreat advantage in the access control system.
Contrast to the contact acquisition mode, the direction, position and shooting distancebetween the palm and the imaging device is uncertain when collecting palm image withcontactless acquisition mode. There are two solutions. One is to normalize the palm image.Another is to extract the translation, rotation and scaling invariant hand feature. Thenormalization changes some properties of the original image that may affect the featureextraction. At the same time, the normalization process also increases the running time. Sothis thesis chooses the latter program.
Main works and results of this thesis are as follows.
(1) In order to select the stable reference point of palm, a palm localization methodbased on inscribed circle is proposed in this thesis. It chooses the circle center as the palmreference point. In order to ensure the inscribed circle is unique, the inscribed circle isdesigned to meet the following criterion: the inscribed circle is tangent to both side of thepalm contour and through the junction point of middle finger and ring finger. By thesymmetry of the circle, the perpendicular bisector that through any two points on theboundary will pass through the circle center and the tangent will be perpendicular to theradius that pass through the tangent point. According to these natures, this methoddetermines the centres and radiuses of inscribes circle by detecting a boundary point in the palm contour lines of the lateral index finger and lateral pinkie outside respectively. Finally,it judges the positioning stability by the standard deviation of gray difference surfacewithin inscribes circle. The more similar the image within inscribes circle, the higher thepositioning stability, and the smaller the standard deviation. The positioning method isverified based on self-build image database.The positioning stability of the proposedmethod is0.751and the average localization time is1116ms. The positioning stability oftraditional inscribes circle positioning method is0.837and the average localization timeis1555ms. Experimental results demonstrate that the proposed method can sresolve theproblem of palm positioning.Compared with traditional methods, the proposed method hashigher positioning accuracy but it need fewer localization time.
(2) In this thesis, the relative positions of the vein crossover points and the inscribecircle center are constructed into a set rotation, translation, scaling invariant features.Firstly, the inscribed circle of palm is obtained. The relative radius and relative angle isdefined by the use of the intersection point inside circle and the circle center. Then, thetwo-dimensional feature vector space is established by the radius and angle parameters.And image is converted to a series of feature points in the feature space. Finally, similarityof the distribution structure of feature points in the feature vector space is taken as thematching basis. Use two methods to evaluate the effectiveness of the features. On the onehand, it is to analyze the stability of the features by match the original image and the imageafter rotation and scaling. Experimental results show that the rotation and scaling have noimpact on the constructed palm features. On the other hand, it is to analyze the uniquenessof the features. The performance of the proposed method is verified by self-build imagedatabase.When thumb naturally stretch and four fingers close, the equal error rate(EER) is0.96%.When five fingers naturally stretch, the equal error rate(EER) is4.91%.Experimental results show that the method can obtain good recognition effect. It hasinvariant to scaling, rotation and translation and fault tolerance of feature pointextraction.This method is suitable for palm identification instruments that need smallerdata storage space, because it can obtain better recognition results by a small number offeatures.
(3) This thesis proposes a novel feature extraction method which can reflects thegeometric features of palmprint and palm vein without being affected by the scaling,rotation and translation. Firstly, several radiation segments are made between the inscribedcircle center and circumference. The reference direction is the direction of the circle center with the junction point of middle finger and ring finger. Meanwhile, the gradient value ofpixels in the feature line segment is calculated by creating template. The feature vectorspace is established by the relative radius of feature line segment’s centroids. Secondly, thepalm image database is established based on the practical application environment. Thefeature stability in different size of sub-template and recognition performance in differentnumber of feature line segments is analyzed. When the size of sub-template is7×7, thefeature stability is the best.When the number of feature line is sixty, the recognitionperformance is relatively stable and not any more significantly increased.Finally, use twomethods to evaluate the effectiveness of the features.1) The stability of the features.Onehundred and seventy hand images is rotated and scaled.The matching rate which theoriginal image and transformed images is greater than97%;2) The uniqueness of thefeatures.When the size of sub-template is equal to seven and the number of feature linesegments is sixty, the equal error rate(EER) is less than0.4%and feature extraction time is0.0019s. The experimental results show that the method can extract out stablecharacteristics whenever the hand image is scaled, rotated or translated. And computingspeed is faster.This method is suitable for palm identification device which has higherrequirements for real-time.
引文
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