WO2015180460A1 - 掌静脉识别智能系统 - Google Patents
掌静脉识别智能系统 Download PDFInfo
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- WO2015180460A1 WO2015180460A1 PCT/CN2014/094463 CN2014094463W WO2015180460A1 WO 2015180460 A1 WO2015180460 A1 WO 2015180460A1 CN 2014094463 W CN2014094463 W CN 2014094463W WO 2015180460 A1 WO2015180460 A1 WO 2015180460A1
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- 210000003462 vein Anatomy 0.000 title claims abstract description 113
- 238000012549 training Methods 0.000 claims abstract description 20
- 230000003287 optical effect Effects 0.000 claims abstract description 18
- 238000003384 imaging method Methods 0.000 claims abstract description 15
- 238000005286 illumination Methods 0.000 claims abstract description 14
- 230000005540 biological transmission Effects 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims description 10
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000012545 processing Methods 0.000 claims description 6
- 238000012360 testing method Methods 0.000 claims description 6
- 238000012795 verification Methods 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 3
- 230000035945 sensitivity Effects 0.000 claims 1
- 230000007613 environmental effect Effects 0.000 abstract description 3
- 230000036632 reaction speed Effects 0.000 abstract description 2
- 230000002452 interceptive effect Effects 0.000 abstract 1
- 238000005299 abrasion Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 210000002837 heart atrium Anatomy 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000002792 vascular Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/14—Vascular patterns
Definitions
- the invention belongs to the field of biometric identification, and more particularly to a palm vein recognition intelligent system for intelligent recognition.
- the vein is a blood vessel that conducts blood to the heart. It starts from the capillaries and stops at the atria. The superficial veins can be seen under the skin.
- the palm vein as the name implies, is the internal vein of the palm.
- Palm vein recognition is a kind of vein recognition, which belongs to biometric identification. The palm vein recognition system first obtains the palm vein distribution map through the vein recognition instrument, and extracts the feature value from the palm vein distribution map according to the special comparison algorithm, and obtains the characteristic value through the infrared CCD camera. Images of the fingers, palms, and dorsal veins of the hand store the digital images of the veins in a computer system to store the feature values.
- the vein map is taken in real time to extract the feature values, and the advanced filtering, image binarization and refinement methods are used to extract the features of the digital image, and the venous feature values are stored in the host, and a complex matching algorithm is used.
- the venous features are matched to identify individuals and confirm their identity.
- the palm vein When the palm vein is used for identity authentication, the image features of the palm vein are acquired, which is a feature that exists only when the palm is in the living body. In this system, the non-living palm is not able to obtain the characteristics of the vein image, and thus cannot be identified, and thus cannot be faked.
- the palm vein for identity authentication the image of the vein image inside the palm is acquired, not the image feature of the palm surface. Therefore, there is no recognition obstacle due to damage, abrasion, dryness or too wet of the palm surface.
- the palm vein When the palm vein is used for identity authentication and the palm vein image is obtained, the palm does not need to be in contact with the device, and the recognition can be completed by gently releasing it.
- This method has no unsanitary problems when the hand touches the device and the safety problem caused by the surface features of the finger being copied, and avoids the psychological discomfort that is considered as the object of examination, and does not recognize the dirt after being contaminated. .
- the palm vein because the vein is located inside the palm, the influence of external factors such as temperature is negligible and is suitable for almost all users. User acceptance is good.
- this non-invasive scanning process is simple and natural, reducing the user's resistance to fear of hygiene or use. Because of the previous characteristics of living body recognition, internal features and non-contact, it is difficult to forge the user's palm vein features. Therefore, the palm vein recognition system has a high safety level and is particularly suitable for use in places with high safety requirements.
- the following technical problems still exist in the palm vein (1) it belongs to the internal physiological characteristics and will not wear out. It is difficult to forge and has high security. (2) The vascular characteristics are usually more obvious, easy to identify, and good in anti-interference. (3) Non-contact measurement can be realized, which is hygienic and easy to accept for users. (4) It is not easily affected by surface scratches or oil stains.
- the disadvantages of the above technology are that the collection device has special requirements, the design is relatively complicated, and the manufacturing cost is high.
- the present invention solves the problem of low accuracy caused by environmental interference or different palm placement angles in the prior art, and proposes a palm vein recognition intelligence for intelligent recognition. system.
- the palm vein recognition intelligent system of the invention comprises an imaging circuit, a lighting circuit, an identification module and a wireless transmission module;
- the imaging circuit comprises a CCD camera, an optical lens and a filter;
- the illumination circuit is composed of a near-infrared LED;
- the identification module comprises an identification The unit, the electronic ranging unit and the voice unit, the wireless transmission module transmits the video information and the control signal to the computer and communicates with the computer, wherein the identification module recognizes the palm vein according to the following steps:
- the first step is to train and project the palm vein image, and five candidate palm vein images are obtained by matching the classifier;
- the verification criterion is determined by matching the number of key points, and the palm vein descriptor with the largest number of matching points is set as the most probable item, and the target palm vein image is obtained by feature matching.
- the optimal projection matrix obtained by training in the first step is as follows:
- W is the optimal projection matrix, where S w and S b are defined as follows:
- the Euclidean distance based on the nearest neighbor rule is used to classify the palm vein
- the negative sample that is, the non-training palm vein image and the non-palm vein image are used to define the threshold of the palm vein verification. If the minimum score is below the defined threshold, the input data is considered to be a known positive candidate palm vein, otherwise it is considered a negative palm vein image or an unknown palm vein image.
- the image of the palm vein and the image of the palm vein with the query are pre-processed separately.
- the optical optical lens in the imaging circuit is a large field of view optical lens
- the filter adopts an infrared filter with a cutoff wavelength of 720 nm
- the optical lens is mounted on the near infrared camera, and the infrared filter is embedded.
- the front panel of the housing in front of the optical lens.
- the identification module measures the user's palm distance information through the electronic ranging unit, and the control circuit sends a corresponding instruction to the voice unit, and gives a prompt of the user's moving direction through the voice unit.
- the electronic ranging unit in the identification module is an ultrasonic or infrared ranging module, and the user palm distance information is measured in real time;
- the voice unit uses a dedicated voice processing chip and is equipped with a high-sensitivity speaker, and the voice that needs to be broadcast has been burned into the voice processing in advance.
- the FLASH of the chip is an ultrasonic or infrared ranging module, and the user palm distance information is measured in real time;
- the voice unit uses a dedicated voice processing chip and is equipped with a high-sensitivity speaker, and the voice that needs to be broadcast has been burned into the voice processing in advance.
- the single chip microcomputer in the identification module is used as a main control chip of the system, and reads the distance information of the electronic ranging unit in real time and determines whether the palm of the user is within a clear imageable range; if the single chip exceeds the clear imaging range, the single chip transmits to the voice unit.
- the corresponding command controls the voice unit to broadcast the corresponding voice to prompt the user to move; according to the needs of the actual collection environment, the illumination source can be adjusted; the computer sends a corresponding dimming command to the single-chip microcomputer, and the PWM pulse width modulation is performed after the single-chip computer receives the command or
- the IO port level change controls the brightness and quantity of the illumination near-infrared LED to adjust the illumination brightness.
- the reaction speed can be within 8 s, and the interference of environmental factors on palm vein recognition can be accurately eliminated, and the accuracy and efficiency of palm vein recognition can be improved.
- Figure 1 is a flow chart of the palm vein recognition of the present invention.
- the palm vein recognition intelligent system comprises an imaging circuit, a lighting circuit, an identification module, a wireless transmission module; the imaging circuit comprises a CCD camera, an optical lens, and a filter; wherein the optical optical lens in the imaging circuit is a large field of view optical lens
- the filter uses an infrared filter with a cutoff wavelength of 720 nm.
- the optical lens is mounted on a near-infrared camera.
- the infrared filter is embedded in the front panel of the housing and is located in front of the optical lens.
- the illumination circuit is composed of a near-infrared LED; the identification module includes an electronic ranging unit and a voice unit, and the wireless transmission module transmits the video information and the control signal to the computer and communicates with the computer, and the identification module measures the distance information of the user's palm through the electronic ranging unit, The phase is sent by the control circuit to the speech unit It should be instructed to give a hint of the user's direction of movement through the speech unit.
- the electronic ranging unit in the identification module is an ultrasonic or infrared ranging module, which measures the distance information of the user's palm in real time; the voice unit uses a dedicated voice processing chip and is equipped with a high-sensitivity speaker, and the voice that needs to be broadcast has been burned into the FLASH of the voice processing chip in advance.
- the single chip in the identification module is used as the main control chip of the system, which reads the distance information of the electronic ranging unit in real time and determines whether the palm of the user is within the clear imageable range; if the single chip exceeds the clear imaging range, the corresponding instruction is sent to the voice unit. Control the voice unit to broadcast the corresponding voice to prompt the user to move; according to the needs of the actual collection environment, the illumination source can be adjusted; the computer sends a corresponding dimming command to the single chip microcomputer, and the PWM pulse width modulation or IO port is performed after the single chip receives the command.
- the flat change controls the brightness and quantity of the illumination near-infrared LEDs to adjust the illumination brightness.
- the identification module identifies the palm vein by following these steps:
- the first step is to pre-process the palm vein image and the palm vein image with query, feature extraction, training and projection, and the palm vein travel projection and data matrix after training.
- the palm vein images are trained and projected, and five candidate palm vein images are obtained by matching the classifier.
- the optimal projection matrix obtained by training is as follows:
- W is the optimal projection matrix, where S w and S b are defined as follows:
- the verification criterion is determined by matching the number of key points, and the palm vein descriptor with the largest number of matching points is set as the most probable item, and the target palm vein image is obtained by feature matching.
- the Euclidean distance based on the nearest neighbor rule is used to classify the palm vein
- the negative sample, ie the non-training palm vein image and the non-palm vein image are used to define the threshold for palm vein verification, if the minimum score is below the defined threshold, then
- the input data is considered to be a known positive candidate palm vein, otherwise it is considered to be a negative palm vein image or an unknown palm vein image.
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- Vascular Medicine (AREA)
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
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Abstract
本发明属于生物识别领域，更具体地涉及一种用于智能识别的掌静脉识别智能系统。包括成像电路、照明电路、识别模块、无线传输模块；所述成像电路包括CCD摄像机、光学镜头、滤光片；照明电路由近红外LED组成；识别模块包括识别单元、电子测距单元和语音单元，无线传输模块将视频信息与控制信号传送到电脑并实现与电脑通讯。通过本发明的训练和特征匹配方式，能够使反应速度在8s之内，并能够准确的排除环境因素对掌静脉识别的干扰，提高掌静脉识别的准确度和效率。
Description
本发明属于生物识别领域，更具体地涉及一种用于智能识别的掌静脉识别智能系统。
静脉是导血回心的血管，起于毛细血管，止于心房，表浅静脉在皮下可以看见。掌静脉，顾名思义，就是手掌内静脉。掌静脉识别是静脉识别的一种，属于生物识别，掌静脉识别系统就是首先通过静脉识别仪取得个人掌静脉分布图，从掌静脉分布图依据专用比对算法提取特征值，通过红外线CCD摄像头获取手指、手掌、手背静脉的图像，将静脉的数字图像存贮在计算机系统中，将特征值存储。静脉比对时，实时采取静脉图，提取特征值，运用先进的滤波、图像二值化、细化手段对数字图像提取特征，同存储在主机中静脉特征值比对，采用复杂的匹配算法对静脉特征进行匹配，从而对个人进行身份鉴定，确认身份。
用掌静脉进行身份认证时，获取的是掌静脉的图像特征，是掌活体时才存在的特征。在该系统中，非活体的手掌是得不到静脉图像特征的，因而无法识别，从而也就无法造假。用掌静脉进行身份认证时，获取的是手掌内部的静脉图像特征，而不是手掌表面的图像特征。因此，不存在任何由于手掌表面的损伤、磨损、干燥或太湿等带来的识别障碍。用掌静脉进行身份认证，获取手掌静脉图像时，手掌无须与设备接触，轻轻一放，即可完成识别。这种方式没有手接触设备时的不卫生的问题以及手指表面特征可能被复制所带来的安全问题，并避免了被当作审查对象的心理不适，同时也不会因脏物污染后无法识别。手掌静脉方式由于静脉位于手掌内部，气温等外部因素的影响程度可以忽略不计，几乎适用于所有用户。用户接受度好。除了无需与扫描器表面发生直接接触以外，这种非侵入性的扫描过程既简单又自然，减轻了用户由于担心卫生程度或使用麻烦而可能存在的抗拒心理。因为有了前面的活体识别、内部特征和非接触式3个方面的特征，确保了使用者的掌静脉特征很难被伪造。所以掌静脉识别系统安全等级高，特别适合于安全要求高的场所使用。传统的静脉识别算法以及如何用昂贵的DSP处理器处理浮点运算和提高实时性要求，缩短识别时间，目前掌静脉还存在以下技术问题待解决：(1)属于内生理特征，不会磨损，较难伪造，具有很高安全性。(2)血管特征通常更明显，容易辨识，抗干扰性好。(3)可实现非接触式测量，卫生性好，易于为用户接受。(4)不易受手表面伤痕或油污的影响。以上技术存在的缺点是：采集设备有特殊要求，设计相对复杂，制造成本高。
发明内容
1、本发明的目的。
本发明为了提高掌静脉的识别准确度，解决现有技术中由于环境干扰或者手掌的摆放角度不同而导致的准确度不高的问题，而提出的一种用于智能识别的掌静脉识别智能系统。
2、本发明所采用的技术方案。
本发明的掌静脉识别智能系统，包括成像电路、照明电路、识别模块、无线传输模块；所述成像电路包括CCD摄像机、光学镜头、滤光片；照明电路由近红外LED组成；识别模块包括识别单元、电子测距单元和语音单元，无线传输模块将视频信息与控制信号传送到电脑并实现与电脑通讯，其中识别模块识别掌静脉按照以下步骤进行：
第一步、训练及投影掌静脉图像，通过分类器的匹配得到五个候选的掌静脉图像；
第二步、分类器中的五个候选掌静脉图像中找到最佳测试图像：
a、加载所有掌静脉图像训练集，与候选掌静脉对应；
b、利用融合掌静脉描述从训练集中提取每张掌静脉的形变；
c、提取掌静脉测试图像的形变，表示为Dq；
d、用Dq与之前的五个候选掌静脉图像相匹配，找到匹配关键点数目
第三步、由匹配关键点数目来确定验证准则，设定匹配点数目最大的掌静脉描述符是最有可能的项，通过特征匹配，得到目标掌静脉图像。
优选的，所述的第一步中训练得到的最佳投影矩阵如下：
W为最佳投影矩阵，其中Sw和Sb的定义如下：
优选的，所述的第三步中，对于匹配过程，使用基于最近邻规则的欧氏距离对掌静脉分类，负样本即非训练掌静脉图像和非掌静脉图像用于定义掌静脉验证的阈值，如果最小得分低于定义的阈值，则认为输入数据是已知的正的候选掌静脉，否则认为是负掌静脉图像或未知掌静脉图像。
优选的，所述的第一步中首先对掌静脉的图像和带查询的掌静脉图像预处理、分别进行
特征提取、训练及投影、对训练后的掌静脉行程投影和数据矩阵。
优选的，所述的成像电路中光学光学镜头为大视场光学镜头，滤光片采用截止波长为720nm的透红外滤光片，光学镜头安装在近红外摄像机上，透红外滤光片内嵌在外壳前面板上，位于光学镜头前方。
优选的，所述的识别模块通过电子测距单元测量用户手掌距离信息，由控制电路向语音单元发送相应指令，通过语音单元给出用户移动方向的提示。
优选的，识别模块中的电子测距单元是超声波或红外测距模块，实时测量用户手掌距离信息；语音单元采用专用语音处理芯片并配备高灵敏度喇叭，需要播报的语音已经提前烧录入语音处理芯片的FLASH中。
优选的，识别模块中的的单片机用作系统的主控芯片，它实时读取电子测距单元距离信息并判断用户手掌是否在可清晰成像范围内；如果超出清晰成像范围单片机则向语音单元发送相应的指令控制语音单元播报相应的语音来提示用户进行移动；根据实际采集环境的需要，照明光源可以进行调节；计算机给单片机发送相应的调光指令，单片机接到命令后进行PWM脉宽调制或IO口电平变化控制照明近红外LED的亮度和数量，从而调节照明亮度。
3、本发明的有益效果。
通过本发明的训练和特征匹配方式，能够使反应速度在8s之内，并能够准确的排除环境因素对掌静脉识别的干扰，提高掌静脉识别的准确度和效率。
图1为本发明的掌静脉识别流程图。
为了使专利局的审查员尤其是公众能够更加清楚地理解本发明的技术实质和有益效果，中请人将在下面以实施例的方式作详细说明，但是对实施例的描述均不是对本发明方案的限制，任何依据本发明构思所作出的仅仅为形式上的而非实质性的等效变换都应视为本发明的技术方案范畴。
实施例
掌静脉识别智能系统，包括成像电路、照明电路、识别模块、无线传输模块；所述成像电路包括CCD摄像机、光学镜头、滤光片；所述的成像电路中光学光学镜头为大视场光学镜头，滤光片采用截止波长为720nm的透红外滤光片，光学镜头安装在近红外摄像机上，透红外滤光片内嵌在外壳前面板上，位于光学镜头前方。照明电路由近红外LED组成；识别模块包括电子测距单元和语音单元，无线传输模块将视频信息与控制信号传送到电脑并实现与电脑通讯，识别模块通过电子测距单元测量用户手掌距离信息，由控制电路向语音单元发送相
应指令，通过语音单元给出用户移动方向的提示。识别模块中的电子测距单元是超声波或红外测距模块，实时测量用户手掌距离信息；语音单元采用专用语音处理芯片并配备高灵敏度喇叭，需要播报的语音已经提前烧录入语音处理芯片的FLASH中。识别模块中的的单片机用作系统的主控芯片，它实时读取电子测距单元距离信息并判断用户手掌是否在可清晰成像范围内；如果超出清晰成像范围单片机则向语音单元发送相应的指令控制语音单元播报相应的语音来提示用户进行移动；根据实际采集环境的需要，照明光源可以进行调节；计算机给单片机发送相应的调光指令，单片机接到命令后进行PWM脉宽调制或IO口电平变化控制照明近红外LED的亮度和数量，从而调节照明亮度。
识别模块识别掌静脉按照以下步骤进行：
第一步、首先对掌静脉的图像和带查询的掌静脉图像预处理、分别进行特征提取、训练及投影、对训练后的掌静脉行程投影和数据矩阵。训练及投影掌静脉图像，通过分类器的匹配得到五个候选的掌静脉图像，训练得到的最佳投影矩阵如下：
W为最佳投影矩阵，其中Sw和Sb的定义如下：
第二步、分类器中的五个候选掌静脉图像中找到最佳测试图像：
a、加载所有掌静脉图像训练集，与候选掌静脉对应；
b、利用融合掌静脉描述从训练集中提取每张掌静脉的形变；
c、提取掌静脉测试图像的形变，表示为Dq；
d、用Dq与之前的五个候选掌静脉图像相匹配，找到匹配关键点数目
第三步、由匹配关键点数目来确定验证准则，设定匹配点数目最大的掌静脉描述符是最有可能的项，通过特征匹配，得到目标掌静脉图像。对于匹配过程，使用基于最近邻规则的欧氏距离对掌静脉分类，负样本即非训练掌静脉图像和非掌静脉图像用于定义掌静脉验证的阈值，如果最小得分低于定义的阈值，则认为输入数据是已知的正的候选掌静脉，否则认为是负掌静脉图像或未知掌静脉图像。
Claims (8)
- 一种掌静脉识别智能系统，其特征在于：包括成像电路、照明电路、识别模块、无线传输模块；所述成像电路包括CCD摄像机、光学镜头、滤光片；照明电路由近红外LED组成；识别模块包括识别单元、电子测距单元和语音单元，无线传输模块将视频信息与控制信号传送到电脑并实现与电脑通讯，其中识别模块识别掌静脉按照以下步骤进行：第一步、训练及投影掌静脉图像，通过分类器的匹配得到五个候选的掌静脉图像；第二步、分类器中的五个候选掌静脉图像中找到最佳测试图像：a、加载所有掌静脉图像训练集，与候选掌静脉对应；b、利用融合掌静脉描述从训练集中提取每张掌静脉的形变；c、提取掌静脉测试图像的形变，表示为Dq；d、用Dq与之前的五个候选掌静脉图像相匹配，找到匹配关键点数目第三步、由匹配关键点数目来确定验证准则，设定匹配点数目最大的掌静脉描述符是最有可能的项，通过特征匹配，得到目标掌静脉图像。
- 根据权利要求1所述的掌静脉识别智能系统，其特征在于：所述的第一步中训练得到的最佳投影矩阵如下：
W为最佳投影矩阵，其中Sw和Sb的定义如下：
- 根据权利要求1所述的掌静脉识别智能系统，其特征在于：所述的第三步中，对于匹配过程，使用基于最近邻规则的欧氏距离对掌静脉分类，负样本即非训练掌静脉图像和非掌静脉图像用于定义掌静脉验证的阈值，如果最小得分低于定义的阈值，则认为输入数据是已知的正的候选掌静脉，否则认为是负掌静脉图像或未知掌静脉图像。
- 根据权利要求1、2、3任一所述的掌静脉识别智能系统，其特征在于：所述的第一步中首先对掌静脉的图像和带查询的掌静脉图像预处理、分别进行特征提取、训练及投影、对训练后的掌静脉行程投影和数据矩阵。
- 根据权利要求1所述的掌静脉识别智能系统，其特征在于：所述的成像电路中光学光 学镜头为大视场光学镜头，滤光片采用截止波长为720nm的透红外滤光片，光学镜头安装在近红外摄像机上，透红外滤光片内嵌在外壳前面板上，位于光学镜头前方。
- 根据权利要求1所述的掌静脉识别智能系统，其特征在于：所述的识别模块通过电子测距单元测量用户手掌距离信息，由控制电路向语音单元发送相应指令，通过语音单元给出用户移动方向的提示。
- 根据权利要求1所述的掌静脉识别智能系统，其特征在于：识别模块中的电子测距单元是超声波或红外测距模块，实时测量用户手掌距离信息；语音单元采用专用语音处理芯片并配备高灵敏度喇叭，需要播报的语音已经提前烧录入语音处理芯片的FLASH中。
- 如权利要求1或6所述的掌静脉识别智能系统，其特征在于：识别模块中的的单片机用作系统的主控芯片，它实时读取电子测距单元距离信息并判断用户手掌是否在可清晰成像范围内；如果超出清晰成像范围单片机则向语音单元发送相应的指令控制语音单元播报相应的语音来提示用户进行移动；根据实际采集环境的需要，照明光源可以进行调节；计算机给单片机发送相应的调光指令，单片机接到命令后进行PWM脉宽调制或IO口电平变化控制照明近红外LED的亮度和数量，从而调节照明亮度。
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