技术领域technical field
本发明涉及信息处理技术领域，尤其涉及一种掌纹识别方法、装置和终端设备。The invention relates to the technical field of information processing, in particular to a palmprint recognition method, device and terminal equipment.
背景技术Background technique
随着互联网技术的高速发展，利用生物特征对用户进行掌纹识别已经逐渐深入到人们日常生活当中。其中，生物特征是指唯一的可以测量或可自动识别和验证的生理特征或行为方式，例如指纹、掌型、视网膜、虹膜、声纹等。相关技术中，已经出现了基于对掌纹特征的二维图像的识别，来实现门禁解锁或移动支付等应用。但是，利用平面的二维图像进行识别，受到指纹识别传感器的限制，需要用户将手指按压在指纹识别传感器上进行识别，且容易被污渍、水等影响，导致识别准确率降低。With the rapid development of Internet technology, the use of biometrics to identify users' palm prints has gradually penetrated into people's daily life. Among them, biometrics refer to the only physiological characteristics or behaviors that can be measured or automatically recognized and verified, such as fingerprints, palms, retinas, irises, voiceprints, etc. In related technologies, applications such as access control unlocking or mobile payment have been implemented based on recognition of two-dimensional images of palmprint features. However, the use of flat two-dimensional images for recognition is limited by the fingerprint recognition sensor, which requires the user to press the finger on the fingerprint recognition sensor for recognition, and is easily affected by stains, water, etc., resulting in a reduction in recognition accuracy.
发明内容Contents of the invention
本发明提供一种掌纹识别方法、装置和终端设备，以解决现有技术中，进行二位图像的掌纹识别时，识别准确率低的问题。The present invention provides a palmprint recognition method, device and terminal equipment to solve the problem of low recognition accuracy when performing palmprint recognition of two-dimensional images in the prior art.
本发明实施例提供一种掌纹识别方法，包括：向用户的手掌投射结构光，并获取经过所述手掌的结构光图像；根据所述结构光图像生成所述手掌对应的三维模型；从所述三维模型中提取对应的掌纹特征信息；将所述掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配，如果匹配成功，则确定用户掌纹识别成功。An embodiment of the present invention provides a palmprint recognition method, including: projecting structured light to the palm of the user, and acquiring a structured light image passing through the palm; generating a three-dimensional model corresponding to the palm according to the structured light image; Extract the corresponding palmprint feature information from the three-dimensional model; match the palmprint feature information with the sample palmprint feature information in the preset palmprint model library, and if the matching is successful, then determine that the user's palmprint recognition is successful.
本发明另一实施例提供一种掌纹识别装置，包括：获取模块，用于向用户的手掌投射结构光，并获取经过所述手掌的结构光图像；生成模块，用于根据所述结构光图像生成所述手掌对应的三维模型；提取模块，用于从所述三维模型中提取对应的掌纹特征信息；确定模块，用于将所述掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配，如果匹配成功，则确定用户掌纹识别成功。Another embodiment of the present invention provides a palmprint recognition device, including: an acquisition module, configured to project structured light onto the user's palm, and acquire a structured light image passing through the palm; a generation module, configured to The image generates the three-dimensional model corresponding to the palm; the extraction module is used to extract the corresponding palmprint feature information from the three-dimensional model; the determination module is used to combine the palmprint feature information with the preset palmprint model library The sample palmprint feature information is matched, and if the match is successful, it is determined that the user's palmprint recognition is successful.
本发明还一实施例提供一种非临时性计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现如本发明第一方面实施例所述的掌纹识别方法。Another embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the palmprint recognition method as described in the embodiment of the first aspect of the present invention is implemented.
本发明又一实施例提供一种终端设备，包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，本发明第一方面实施例所述的掌纹识别方法。Another embodiment of the present invention provides a terminal device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. The palmprint recognition described in the embodiment of the first aspect of the present invention method.
本发明实施例提供的技术方案可以包括以下有益效果：The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:
向用户的手掌投射结构光，并获取经过手掌的结构光图像，并根据结构光图像生成手掌对应的三维模型，以及从三维模型中提取对应的掌纹特征信息，并将掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配，如果匹配成功，则确定用户掌纹识别成功，提高了掌纹识别的准确率。Project the structured light to the palm of the user, obtain the structured light image passing through the palm, generate a 3D model corresponding to the palm according to the structured light image, and extract the corresponding palmprint feature information from the 3D model, and combine the palmprint feature information with the pre-set The sample palmprint feature information in the set palmprint model database is matched. If the matching is successful, it is determined that the user's palmprint recognition is successful, which improves the accuracy of palmprint recognition.
本发明附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本发明的实践了解到。Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
附图说明Description of drawings
本发明上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解，其中：The above and/or additional aspects and advantages of the present invention will become apparent and easy to understand from the following description of the embodiments in conjunction with the accompanying drawings, wherein:
图1是根据本发明一个实施例的掌纹识别方法的流程图；Fig. 1 is the flow chart of the palmprint recognition method according to one embodiment of the present invention;
图2是根据本发明一个实施例的结构光测量的场景示意图；Fig. 2 is a schematic diagram of a scene of structured light measurement according to an embodiment of the present invention;
图3是根据本发明另一个实施例的掌纹识别方法的流程图；Fig. 3 is the flowchart of the palmprint recognition method according to another embodiment of the present invention;
图4是根据本发明一个实施例的掌纹识别装置的结构框图；Fig. 4 is a structural block diagram of a palmprint recognition device according to an embodiment of the present invention;
图5是根据本发明另一个实施例的掌纹识别装置的结构框图；Fig. 5 is a structural block diagram of a palmprint recognition device according to another embodiment of the present invention;
图6是根据本发明又一个实施例的掌纹识别装置的结构框图；Fig. 6 is a structural block diagram of a palmprint recognition device according to yet another embodiment of the present invention;
图7是根据本发明一个实施例的终端设备的结构示意图；FIG. 7 is a schematic structural diagram of a terminal device according to an embodiment of the present invention;
图8是根据本发明一个实施例的图像处理电路的示意图。FIG. 8 is a schematic diagram of an image processing circuit according to an embodiment of the present invention.
具体实施方式Detailed ways
下面详细描述本发明的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本发明，而不能理解为对本发明的限制。Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
下面参考附图描述本发明实施例的掌纹识别方法、装置和终端设备。The following describes the palmprint recognition method, device and terminal device according to the embodiments of the present invention with reference to the accompanying drawings.
图1是根据本发明一个实施例的掌纹识别方法的流程图。Fig. 1 is a flowchart of a palmprint recognition method according to an embodiment of the present invention.
如图1所示，该掌纹识别方法包括：As shown in Figure 1, this palmprint recognition method comprises:
S101，向用户的手掌投射结构光，并获取经过手掌的结构光图像。S101. Project structured light to a palm of a user, and acquire a structured light image passing through the palm.
针对当前基于二维图像进行掌纹识别，用户掌纹容易受到污渍、水等影响，导致识别准确率低的技术问题，本发明提出了一种基于结构光进行识别的方式，其中，该识别方式可以用于任意通过识别用户掌纹特征应用的场景中，为了便于描述，本发明集中在应用于掌纹识别场景中进行说明。In view of the current palmprint recognition based on two-dimensional images, the user's palmprint is easily affected by stains, water, etc., resulting in low recognition accuracy. The present invention proposes a recognition method based on structured light, wherein the recognition method It can be used in any scene where the features of the user's palmprint are recognized. For the convenience of description, the present invention focuses on the palmprint recognition scene for illustration.
为了提高对用户的掌纹识别的准确率，可利用结构光对用户的手掌进行三维模型的相关信息的采集，比如，激光条纹、格雷码、正弦条纹、或者，非均匀散斑等，由此，由于结构光可以基于手掌的轮廓和掌纹的深度信息对用户进行三维模型的相关信息的采集，相较于仅仅根据按压指纹识别传感器采集指纹的二维图像信息进行识别的方式，准确率更高。In order to improve the accuracy of the user's palmprint recognition, structured light can be used to collect information about the 3D model of the user's palm, such as laser stripes, gray codes, sinusoidal stripes, or non-uniform speckle, etc. , because structured light can collect relevant information of the user's 3D model based on the outline of the palm and the depth information of the palmprint, compared with the way of identifying only based on the two-dimensional image information of the fingerprint collected by pressing the fingerprint recognition sensor, the accuracy rate is higher. high.
为了使得本领域的技术人员更加清楚的了解，如何根据结构光来采集用户的三维模型的相关信息，下面以一种应用广泛的条纹投影技术为例来阐述其具体原理。在使用面结构光投影的时候，如图2所示，通过计算机编程产生正弦条纹，将该正弦条纹通过投影设备投影至被测物，利用摄像头拍摄条纹受物体调制的弯曲程度，解调该弯曲条纹得到相位，再将相位转化为高度。当然其中至关重要的一点就是系统的配准，包括摄像头与投影设备的配准，否则很可能会产生误差。具体地，可将弯曲条纹的相位与参考条纹的相位相减得到相位差，该相位差则表征了被测物相对参考面的高度信息，再代入相位与高度转化公式，从而得到待测物体的三维模型。应当理解的是，在实际应用中，根据具体应用场景的不同，本发明实施例中所采用的结构光除了上述条纹之外，还可是其他任意图案。In order to make those skilled in the art understand more clearly how to collect relevant information of a user's 3D model based on structured light, the following uses a widely used fringe projection technology as an example to illustrate its specific principles. When using surface structured light projection, as shown in Figure 2, the sinusoidal fringes are generated by computer programming, and the sinusoidal fringes are projected to the measured object through the projection device, and the degree of curvature of the fringes modulated by the object is captured by the camera, and the curvature is demodulated The fringe gets the phase, and the phase is converted to height. Of course, one of the most crucial points is the registration of the system, including the registration of the camera and the projection device, otherwise errors are likely to occur. Specifically, the phase difference can be obtained by subtracting the phase of the curved fringe from the phase of the reference fringe, which represents the height information of the measured object relative to the reference surface, and then substituted into the phase and height conversion formula to obtain the measured object 3D model. It should be understood that, in practical applications, according to different specific application scenarios, the structured light used in the embodiment of the present invention may be other arbitrary patterns besides the above-mentioned stripes.
在本发明的一个实施例中，向用户的手掌投射结构光，并获取经过手掌的结构光图像。In an embodiment of the present invention, the structured light is projected to the palm of the user, and the structured light image passing through the palm is acquired.
S102，根据结构光图像生成手掌对应的三维模型。S102. Generate a three-dimensional model corresponding to the palm according to the structured light image.
基于结构光的原理可知，可解调结构光图像中变形位置像素对应的相位信息，再将相位信息转化为高度信息，然后根据高度信息获取用户掌纹对应的三维模型。Based on the principle of structured light, it can be known that the phase information corresponding to the deformed position pixel in the structured light image can be demodulated, and then the phase information can be converted into height information, and then the 3D model corresponding to the user's palmprint can be obtained according to the height information.
需要说明的是，根据应用场景的不同，可采用不同的方式基于结构光图像获取三维模型。例如：解调结构光图像中变形位置像素对应的相位信息，将相位信息转化为高度信息，根据高度信息获取与结构光图像对应的用户掌纹对应的三维模型，当然，也可以结合轮廓识别技术，基于用户掌纹对应的三维模型，识别出用户手掌的轮廓，根据该轮廓获取三维模型。It should be noted that, according to different application scenarios, different methods may be used to acquire a 3D model based on a structured light image. For example: demodulate the phase information corresponding to the deformed position pixel in the structured light image, convert the phase information into height information, and obtain the 3D model corresponding to the user's palmprint corresponding to the structured light image according to the height information. Of course, it can also be combined with contour recognition technology , based on the 3D model corresponding to the user's palmprint, the outline of the user's palm is recognized, and the 3D model is obtained according to the outline.
S103，从三维模型中提取对应的掌纹特征信息。S103. Extract corresponding palmprint feature information from the three-dimensional model.
其中，掌纹是人的正面皮肤上凸凹不平产生的纹线。纹线有规律的排列形成不同的纹型。掌纹特征信息可包括纹线的起点、终点、结合点和分叉点等。Among them, palm prints are the lines produced by the unevenness on the frontal skin of a person. The lines are arranged regularly to form different grain types. The palmprint feature information may include the starting point, ending point, joint point and bifurcation point of the ridge line.
S104，将掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配，如果匹配成功，则确定用户掌纹识别成功。S104, matching the palmprint feature information with the sample palmprint feature information in the preset palmprint model library, and if the matching is successful, it is determined that the user's palmprint recognition is successful.
在进行匹配之前，需要预先建立掌纹模型库。具体建立该掌纹模型库的过程与掌纹识别的过程类似。首先，多次采集用户的手掌的结构光图像样本，并生成结构光图像样本对应的掌纹模型样本，然后根据掌纹模型样本建立掌纹模型库。因此，每次采集的样本不一定完全相同，因此可以通过多次采集使得建立的掌纹模型库更加准确。Before matching, a palmprint model library needs to be established in advance. The specific process of establishing the palmprint model library is similar to the process of palmprint recognition. First, multiple structured light image samples of the user's palm are collected, and palmprint model samples corresponding to the structured light image samples are generated, and then a palmprint model library is established according to the palmprint model samples. Therefore, the samples collected each time are not necessarily exactly the same, so the established palmprint model library can be made more accurate through multiple collections.
在进行掌纹识别时，可从获取的三维模型中提取对应的掌纹特征信息，进而，应用预设的掌纹模型库中的样本特征信息对掌纹特征信息进行匹配。如果两者匹配一致，则可确定用户掌纹识别成功。During palmprint recognition, the corresponding palmprint feature information can be extracted from the acquired three-dimensional model, and then the palmprint feature information can be matched with the sample feature information in the preset palmprint model library. If the two matches are consistent, it can be determined that the user's palmprint recognition is successful.
此外，如图3所示，还可包括以下步骤：In addition, as shown in Figure 3, the following steps may also be included:
S105，向掌纹识别成功的用户授权，并执行权限范围内的相应操作。S105, authorize the user whose palmprint recognition is successful, and perform corresponding operations within the scope of authority.
在确定用户掌纹识别成功后，还可向掌纹识别成功的用户授权，并执行权限范围内的相应操作，例如门禁解锁。After it is determined that the user's palmprint recognition is successful, it can also authorize the user whose palmprint recognition is successful, and perform corresponding operations within the scope of authority, such as unlocking the access control.
为了使得本领域的技术人员，对本发明实施例的掌纹识别方法更加清楚，下面结合具体的应用场景进行举例。In order to make the palmprint recognition method of the embodiment of the present invention clearer for those skilled in the art, examples are given below in conjunction with specific application scenarios.
在本示例中，掌纹识别的应用场景是快速支付。用户在购物时，需要进行支付操作，用户可向支付的相关设备伸出手掌。此时设备可向用户手掌的正面投射结构光，生成经过当前用户手掌调制的结构光图像。解调该结构光图像对应的相位信息，得到用户掌纹的三维模型。然后，从用户掌纹的三维模型中提取对应的掌纹特征信息上传至数据库，数据库应用预设的掌纹模型库的样本特征信息对掌纹特征信息进行匹配。在匹配成功后，可验证用户身份合法，最后扣除与用户身份绑定的银行卡中账户的钱。如果匹配不成功，则拒绝该次支付。In this example, the application scenario of palmprint recognition is fast payment. When the user is shopping, he needs to perform a payment operation, and the user can extend his palm to the payment-related device. At this time, the device can project structured light to the front of the user's palm to generate a structured light image modulated by the current user's palm. The phase information corresponding to the structured light image is demodulated to obtain a three-dimensional model of the user's palmprint. Then, the corresponding palmprint feature information is extracted from the three-dimensional model of the user's palmprint and uploaded to the database, and the database applies the sample feature information of the preset palmprint model library to match the palmprint feature information. After the matching is successful, it can be verified that the user's identity is legal, and finally the money in the account in the bank card bound to the user's identity is deducted. If the match is unsuccessful, the payment is rejected.
本发明实施例的掌纹识别方法，向用户的手掌投射结构光，并获取经过手掌的结构光图像，并根据结构光图像生成手掌对应的三维模型，以及从三维模型中提取对应的掌纹特征信息，并将掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配，如果匹配成功，则确定用户掌纹识别成功，提高了掌纹识别的准确率。The palmprint recognition method of the embodiment of the present invention projects structured light to the palm of the user, acquires the structured light image passing through the palm, generates a three-dimensional model corresponding to the palm according to the structured light image, and extracts the corresponding palmprint features from the three-dimensional model information, and match the palmprint feature information with the sample palmprint feature information in the preset palmprint model library. If the matching is successful, it is determined that the user's palmprint recognition is successful, which improves the accuracy of palmprint recognition.
为了实现上述实施例，本发明还提出了一种掌纹识别装置，图4是根据本发明一个实施例的掌纹识别装置的结构框图，如图4所示，该装置包括获取模块100、生成模块200、提取模块300和确定模块400。In order to realize above-mentioned embodiment, the present invention also proposes a kind of palmprint recognition device, Fig. 4 is the structural block diagram of the palmprint recognition device according to an embodiment of the present invention, as shown in Fig. 4, this device comprises acquisition module 100, generation module 200 , extraction module 300 and determination module 400 .
其中，获取模块100，用于向用户的手掌投射结构光，并获取经过手掌的结构光图像；Wherein, the acquiring module 100 is configured to project the structured light to the palm of the user, and acquire the structured light image passing through the palm;
生成模块200，用于根据结构光图像生成手掌对应的三维模型；A generation module 200, configured to generate a three-dimensional model corresponding to the palm according to the structured light image;
提取模块300，用于从三维模型中提取对应的掌纹特征信息；Extraction module 300, for extracting corresponding palmprint characteristic information from three-dimensional model;
确定模块400，用于将掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配，如果匹配成功，则确定用户掌纹识别成功。The determining module 400 is configured to match the palmprint feature information with the sample palmprint feature information in the preset palmprint model library, and if the matching is successful, then determine that the user's palmprint recognition is successful.
在本发明的一个实施例中，如图5是根据本发明另一个实施例的掌纹识别装置的结构框图，如图5所示，该装置还包括建立模块500。In one embodiment of the present invention, FIG. 5 is a structural block diagram of a palmprint recognition device according to another embodiment of the present invention. As shown in FIG. 5 , the device further includes a building module 500 .
其中，建立模块500，用于在将掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配之前，建立掌纹模型库。Wherein, the establishment module 500 is used for establishing a palmprint model library before matching the palmprint feature information with the sample palmprint feature information in the preset palmprint model library.
在本发明的一个实施例中，如图6是根据本发明又一个实施例的掌纹识别装置的结构框图，如图6所示，该装置还包括处理模块600。In one embodiment of the present invention, FIG. 6 is a structural block diagram of a palmprint recognition device according to yet another embodiment of the present invention. As shown in FIG. 6 , the device further includes a processing module 600 .
其中，处理模块600，用于在确定用户掌纹识别成功后，向掌纹识别成功的用户授权，并执行权限范围内的相应操作。Wherein, the processing module 600 is configured to authorize the user whose palmprint recognition is successful after determining that the user's palmprint recognition is successful, and perform corresponding operations within the authority range.
需要说明的是，前述对掌纹识别方法的解释说明，也适用于本发明实施例的掌纹识别装置，本发明实施例中未公布的细节，在此不再赘述。It should be noted that the foregoing explanations of the palmprint recognition method are also applicable to the palmprint recognition device of the embodiment of the present invention, and details not disclosed in the embodiment of the present invention will not be repeated here.
本发明实施例的掌纹识别装置，向用户的手掌投射结构光，并获取经过手掌的结构光图像，并根据结构光图像生成手掌对应的三维模型，以及从三维模型中提取对应的掌纹特征信息，并将掌纹特征信息与预设的掌纹模型库中的样本掌纹特征信息进行匹配，如果匹配成功，则确定用户掌纹识别成功，提高了掌纹识别的准确率。The palmprint recognition device of the embodiment of the present invention projects structured light onto the palm of the user, acquires the structured light image passing through the palm, generates a three-dimensional model corresponding to the palm according to the structured light image, and extracts the corresponding palmprint features from the three-dimensional model information, and match the palmprint feature information with the sample palmprint feature information in the preset palmprint model library. If the matching is successful, it is determined that the user's palmprint recognition is successful, which improves the accuracy of palmprint recognition.
为了实现上述实施例，本发明还提出一种非临时性计算机可读存储介质，其上存储有计算机程序，当该计算机程序被处理器执行时能够实现如前述实施例的掌纹识别方法。In order to realize the above-mentioned embodiments, the present invention also proposes a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the palmprint recognition method as in the above-mentioned embodiments can be realized.
为了实现上述实施例，本发明还提出了一种终端设备。In order to realize the above embodiments, the present invention also proposes a terminal device.
如图7所示，该终端设备包括：处理器71、存储器72、及图像处理电路73。As shown in FIG. 7 , the terminal device includes: a processor 71 , a memory 72 , and an image processing circuit 73 .
其中，存储器72用于存储可执行程序代码；处理器71通过读取存储器72中存储的可执行程序代码，及图像处理电路73对图像进行处理，来实现如前述实施例中的掌纹识别方法。Wherein, memory 72 is used for storing executable program code; Processor 71 is by reading the executable program code stored in memory 72, and image processing circuit 73 processes image, realizes the palmprint recognition method as in the aforementioned embodiment .
具体的，图像处理电路73可以利用硬件和/或软件组件实现，可包括定义ISP(Image Signal Processing，图像信号处理)管线的各种处理单元。Specifically, the image processing circuit 73 may be implemented by using hardware and/or software components, and may include various processing units defining an ISP (Image Signal Processing, image signal processing) pipeline.
图8为一个实施例中图像处理电路的示意图。如图8所示，为便于说明，仅示出与本发明实施例相关的图像处理技术的各个方面。Fig. 8 is a schematic diagram of an image processing circuit in one embodiment. As shown in FIG. 8 , for ease of description, only various aspects of the image processing technology related to the embodiment of the present invention are shown.
如图8所示，图像处理电路包括成像设备810、ISP处理器830和控制逻辑器840。成像设备810可包括具有一个或多个透镜812、图像传感器814的照相机和结构光投射器816。结构光投射器816将结构光投影至被测物。其中，该结构光图案可为激光条纹、格雷码、正弦条纹、或者，随机排列的散斑图案等。图像传感器814捕捉投影至被测物形成的结构光图像，并将结构光图像发送至ISP处理器830，由ISP处理器830对结构光图像进行解调获取被测物的深度信息。同时，图像传感器814也可以捕捉被测物的色彩信息。当然，也可以由两个图像传感器814分别捕捉被测物的结构光图像和色彩信息。As shown in FIG. 8 , the image processing circuit includes an imaging device 810 , an ISP processor 830 and a control logic 840 . Imaging device 810 may include a camera having one or more lenses 812 , an image sensor 814 , and a structured light projector 816 . The structured light projector 816 projects the structured light onto the object under test. Wherein, the structured light pattern may be laser stripes, gray codes, sinusoidal stripes, or randomly arranged speckle patterns and the like. The image sensor 814 captures the structured light image projected onto the measured object, and sends the structured light image to the ISP processor 830, and the ISP processor 830 demodulates the structured light image to obtain the depth information of the measured object. At the same time, the image sensor 814 can also capture the color information of the measured object. Of course, the structured light image and color information of the object under test may also be captured by the two image sensors 814 respectively.
其中，以散斑结构光为例，ISP处理器830对结构光图像进行解调，具体包括，从该结构光图像中采集被测物的散斑图像，将被测物的散斑图像与参考散斑图像按照预定算法进行图像数据计算，获取被测物上散斑图像的各个散斑点相对于参考散斑图像中的参考散斑点的移动距离。利用三角法转换计算得到散斑图像的各个散斑点的深度值，并根据该深度值得到被测物的深度信息。Wherein, taking speckle structured light as an example, the ISP processor 830 demodulates the structured light image, which specifically includes collecting the speckle image of the measured object from the structured light image, and combining the speckle image of the measured object with the reference The image data of the speckle image is calculated according to a predetermined algorithm, and the moving distance of each speckle point in the speckle image on the object under test relative to the reference speckle point in the reference speckle image is obtained. The depth value of each speckle point of the speckle image is converted and calculated by using the triangulation method, and the depth information of the measured object is obtained according to the depth value.
当然，还可以通过双目视觉的方法或基于飞行时差TOF的方法来获取该深度图像信息等，在此不做限定，只要能够获取或通过计算得到被测物的深度信息的方法都属于本实施方式包含的范围。Of course, the depth image information can also be obtained through binocular vision or a method based on time-of-flight TOF, and there is no limitation here, as long as the method that can obtain or calculate the depth information of the measured object belongs to this implementation The range covered by the method.
在ISP处理器830接收到图像传感器814捕捉到的被测物的色彩信息之后，可被测物的色彩信息对应的图像数据进行处理。ISP处理器830对图像数据进行分析以获取可用于确定和/或成像设备810的一个或多个控制参数的图像统计信息。图像传感器814可包括色彩滤镜阵列(如Bayer滤镜)，图像传感器814可获取用图像传感器814的每个成像像素捕捉的光强度和波长信息，并提供可由ISP处理器830处理的一组原始图像数据。After the ISP processor 830 receives the color information of the object under test captured by the image sensor 814, it may process the image data corresponding to the color information of the object under test. ISP processor 830 analyzes the image data to obtain image statistics that may be used to determine and/or control one or more parameters of imaging device 810 . Image sensor 814 may include a color filter array (such as a Bayer filter), and image sensor 814 may obtain light intensity and wavelength information captured with each imaging pixel of image sensor 814 and provide a set of raw images that may be processed by ISP processor 830. image data.
ISP处理器830按多种格式逐个像素地处理原始图像数据。例如，每个图像像素可具有8、10、12或14比特的位深度，ISP处理器830可对原始图像数据进行一个或多个图像处理操作、收集关于图像数据的图像统计信息。其中，图像处理操作可按相同或不同的位深度精度进行。The ISP processor 830 processes raw image data on a pixel-by-pixel basis in various formats. For example, each image pixel may have a bit depth of 8, 10, 12, or 14 bits, and the ISP processor 830 may perform one or more image processing operations on the raw image data, collect image statistics about the image data. Among other things, image processing operations can be performed with the same or different bit depth precision.
ISP处理器830还可从图像存储器820接收像素数据。图像存储器820可为存储器装置的一部分、存储设备、或电子设备内的独立的专用存储器，并可包括DMA(Direct MemoryAccess，直接直接存储器存取)特征。ISP processor 830 may also receive pixel data from image memory 820 . The image memory 820 may be a part of a memory device, a storage device, or an independent dedicated memory in an electronic device, and may include a DMA (Direct Memory Access, Direct Memory Access) feature.
当接收到原始图像数据时，ISP处理器830可进行一个或多个图像处理操作。When raw image data is received, ISP processor 830 may perform one or more image processing operations.
在ISP处理器830获取到被测物的色彩信息和深度信息后，可对其进行融合，得到三维图像。其中，可通过外观轮廓提取方法或轮廓特征提取方法中的至少一种提取相应的被测物的特征。例如通过主动形状模型法ASM、主动外观模型法AAM、主成分分析法PCA、离散余弦变换法DCT等方法，提取被测物的特征，在此不做限定。再将分别从深度信息中提取到被测物的特征以及从色彩信息中提取到被测物的特征进行配准和特征融合处理。这里指的融合处理可以是将深度信息以及色彩信息中提取出的特征直接组合，也可以是将不同图像中相同的特征进行权重设定后组合，也可以有其他融合方式，最终根据融合后的特征，生成三维图像。After the ISP processor 830 acquires the color information and depth information of the object under test, they can be fused to obtain a three-dimensional image. Wherein, the feature of the corresponding object under test may be extracted by at least one of an appearance contour extraction method or a contour feature extraction method. For example, the features of the measured object are extracted by active shape modeling method ASM, active appearance modeling method AAM, principal component analysis method PCA, discrete cosine transform method DCT and other methods, which are not limited here. Then, the features of the measured object extracted from the depth information and the features of the measured object extracted from the color information are subjected to registration and feature fusion processing. The fusion processing referred to here can be to directly combine the features extracted from the depth information and color information, or to combine the same features in different images after setting weights, or there can be other fusion methods, and finally according to the fused features to generate a 3D image.
三维图像的图像数据可发送给图像存储器820，以便在被显示之前进行另外的处理。ISP处理器830从图像存储器820接收处理数据，并对处理数据进行原始域中以及RGB和YCbCr颜色空间中的图像数据处理。三维图像的图像数据可输出给显示器860，以供用户观看和/或由图形引擎或GPU(Graphics Processing Unit，图形处理器)进一步处理。此外，ISP处理器830的输出还可发送给图像存储器820，且显示器860可从图像存储器820读取图像数据。在一个实施例中，图像存储器820可被配置为实现一个或多个帧缓冲器。此外，ISP处理器830的输出可发送给编码器/解码器850，以便编码/解码图像数据。编码的图像数据可被保存，并在显示于显示器860设备上之前解压缩。编码器/解码器850可由CPU或GPU或协处理器实现。Image data for a three-dimensional image may be sent to image memory 820 for additional processing before being displayed. The ISP processor 830 receives the processed data from the image memory 820 and performs image data processing in the original domain and in the RGB and YCbCr color spaces on the processed data. The image data of the three-dimensional image may be output to the display 860 for viewing by the user and/or further processing by a graphics engine or a GPU (Graphics Processing Unit, graphics processor). In addition, the output of the ISP processor 830 can also be sent to the image memory 820 , and the display 860 can read image data from the image memory 820 . In one embodiment, image memory 820 may be configured to implement one or more frame buffers. Also, the output of the ISP processor 830 may be sent to an encoder/decoder 850 for encoding/decoding image data. The encoded image data may be saved and decompressed prior to display on the display 860 device. Encoder/decoder 850 may be implemented by a CPU or GPU or a coprocessor.
ISP处理器830确定的图像统计信息可发送给控制逻辑器840单元。控制逻辑器840可包括执行一个或多个例程(如固件)的处理器和/或微控制器，一个或多个例程可根据接收的图像统计信息，确定成像设备810的控制参数。The image statistics determined by the ISP processor 830 may be sent to the control logic 840 unit. Control logic 840 may include a processor and/or microcontroller executing one or more routines (eg, firmware) that may determine control parameters for imaging device 810 based on received image statistics.
需要说明的是，前述对掌纹识别方法实施例的解释说明也适用于该实施例的终端设备，其实现原理类似，此处不再赘述。It should be noted that the foregoing explanations of the embodiment of the palmprint recognition method are also applicable to the terminal device of this embodiment, and its implementation principles are similar, so details are not repeated here.
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。In the description of this specification, descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific examples", or "some examples" mean that specific features described in connection with the embodiment or example , structure, material or characteristic is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the described specific features, structures, materials or characteristics may be combined in any suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples and features of different embodiments or examples described in this specification without conflicting with each other.
尽管上面已经示出和描述了本发明的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本发明的限制，本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention, those skilled in the art can make the above-mentioned The embodiments are subject to changes, modifications, substitutions and variations.
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| CN201710677627.4ACN107590435A (en) | 2017-08-09 | 2017-08-09 | Palmprint recognition method, device and terminal equipment |
| Application Number | Priority Date | Filing Date | Title |
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| CN201710677627.4ACN107590435A (en) | 2017-08-09 | 2017-08-09 | Palmprint recognition method, device and terminal equipment |
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| CN201710677627.4APendingCN107590435A (en) | 2017-08-09 | 2017-08-09 | Palmprint recognition method, device and terminal equipment |
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