TWI629645B - Optical identification method - Google Patents

Optical identification method Download PDF

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TWI629645B
TWI629645B TW106125735A TW106125735A TWI629645B TW I629645 B TWI629645 B TW I629645B TW 106125735 A TW106125735 A TW 106125735A TW 106125735 A TW106125735 A TW 106125735A TW I629645 B TWI629645 B TW I629645B
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finger image
brightness
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average brightness
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TW201824081A (en
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蕭俊賢
林俊甫
蔡惠民
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曦威科技股份有限公司
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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
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    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
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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
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1365—Matching; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
    • H—ELECTRICITY
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    • H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
    • 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
    • G06V40/12—Fingerprints or palmprints
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Abstract

一種光學識別方法，其中包含：投射光至手指以產生一反射光；以一像素感測單元，接收反射光以產生多個手指影像；以及根據像素感測單元擷取手指影像的所需曝光時間或平均亮度，判斷手指影像是否具有一活體特徵；其中，當手指影像具有活體特徵時，則根據手指影像產生識別資訊；或者當手指影像不具有活體特徵時，則不根據手指影像產生識別資訊，且像素感測單元可停止產生後續手指影像。An optical recognition method includes: projecting light onto a finger to generate a reflected light; using a pixel sensing unit to receive the reflected light to generate a plurality of finger images; and an exposure time required to capture a finger image according to the pixel sensing unit Or average brightness to determine whether the finger image has a living feature; where the finger image has a living feature, identification information is generated based on the finger image; or when the finger image does not have a living feature, identification information is not generated based on the finger image, And the pixel sensing unit can stop generating subsequent finger images.

Description

光學識別方法Optical identification method

本發明係有關一種光學識別方法，此光學識別方法藉由同一像素感測單元與同一光源，以感測手指影像之活體特徵與指紋特徵，藉此而在不增加成本的情況下，提高防偽功能。The invention relates to an optical identification method. The optical identification method uses the same pixel sensing unit and the same light source to sense the characteristics of the living body and fingerprint of the finger image, thereby improving the anti-counterfeiting function without increasing the cost. .

使用指紋特徵來進行身分辨識，已為常用之技術。但，先前技術之光學識別系統，例如光學式感測器，雖可判斷手指指紋，然而現代的指紋仿製技術不斷進步，雖然使用者未在場，但藉由仿製之指紋可欺瞞光學識別系統，讓光學識別系統誤判斷使用者正在使用系統。因此，純粹以指紋紋路來判斷，仍有辨識錯誤的風險。The use of fingerprint characteristics for identity recognition has become a common technique. However, although the prior art optical identification systems, such as optical sensors, can judge finger fingerprints, modern fingerprint imitation technology continues to advance. Although the user is not present, the imitation fingerprint can deceive the optical identification system. Let the optical recognition system misjudge that the user is using the system. Therefore, purely based on fingerprints, there is still a risk of misidentification.

此外，先前技術之電容式感測器，僅能判斷手指之按壓動作以計算手指之觸碰與運動，但無法判斷手指之指紋、更無法根據指紋特徵來進行身分辨識。In addition, the capacitive sensor of the prior art can only determine the pressing action of the finger to calculate the touch and movement of the finger, but cannot determine the fingerprint of the finger, nor can it perform identity recognition based on the characteristics of the fingerprint.

就其中一個觀點言，本發明提供了一種光學識別方法，其包含：投射光至一手指以產生一反射光；以一像素感測單元，接收反射光以產生多個手指影像；以及根據像素感測單元擷取手指影像的所需曝光時間或平均亮度，判斷手指影像是否具有一活體特徵；其中，當手指影像具有活體特徵時，則根據手指影像產生識別資訊；或者當手指影像不具有活體特徵時，則不根據手指影像產生識別資訊，且像素感測單元可停止產生後續手指影像。According to one of the viewpoints, the present invention provides an optical recognition method including: projecting light onto a finger to generate a reflected light; using a pixel sensing unit to receive the reflected light to generate a plurality of finger images; and according to the pixel sense The measuring unit captures the required exposure time or average brightness of the finger image to determine whether the finger image has a living feature; wherein, when the finger image has a living feature, identification information is generated based on the finger image; or when the finger image does not have a living feature , The identification information is not generated based on the finger image, and the pixel sensing unit can stop generating subsequent finger images.

一實施例中， 光學識別方法又包含：判斷像素感測單元擷取之手指影像，是否具有一運動狀態，其中當手指影像具有運動狀態時，像素感測單元停止產生手指影像。In one embodiment, the optical recognition method further includes: determining whether the finger image captured by the pixel sensing unit has a motion state, and when the finger image has a motion state, the pixel sensing unit stops generating a finger image.

一實施例中，像素感測單元具有一感測動態範圍，並根據感測動態範圍決定各手指影像之所需曝光時間，其中判斷手指影像是否具有一活體特徵之步驟包含：判斷各手指影像之所需曝光時間是否落在一曝光時間門檻值所定義的範圍內，如是，則判斷手指影像具有活體特徵；如否，則判斷手指影像不具有活體特徵。In one embodiment, the pixel sensing unit has a sensing dynamic range, and determines a required exposure time for each finger image according to the sensing dynamic range. The step of determining whether the finger image has a living feature includes: determining the Whether the required exposure time falls within a range defined by an exposure time threshold. If so, it is judged that the finger image has living features; if not, it is judged that the finger image does not have living features.

一實施例中，曝光時間門檻值包含一曝光時間上限門檻值、或包含一曝光時間下限門檻值、或包含曝光時間上限及下限門檻值。In an embodiment, the exposure time threshold includes an upper exposure time threshold, or an lower exposure time threshold, or an upper exposure time threshold and a lower threshold value.

一實施例中，像素感測單元具有一感測曝光時間，以接收反射光並產生手指影像，手指影像根據感測曝光時間具有平均亮度，其中判斷手指影像是否具有一活體特徵之步驟包含：判斷手指影像的平均亮度是否落在一亮度門檻值所定義的範圍內，如是，則判斷手指影像具有活體特徵；如否，則判斷手指影像不具有活體特徵。In one embodiment, the pixel sensing unit has a sensing exposure time to receive reflected light and generate a finger image. The finger image has an average brightness according to the sensing exposure time. The step of determining whether the finger image has a living feature includes: determining Whether the average brightness of the finger image falls within a range defined by a brightness threshold. If so, it is judged that the finger image has living features; if not, it is judged that the finger image does not have living features.

一實施例中，亮度門檻值包含一亮度上限門檻值、或包含一亮度下限門檻值、或包含亮度上限及下限門檻值。In one embodiment, the brightness threshold value includes an upper brightness threshold value, or a lower brightness threshold value, or an upper brightness threshold and a lower threshold value.

一實施例中，前述之根據像素感測單元擷取手指影像的平均亮度，判斷手指影像是否具有活體特徵之步驟包含：根據各手指影像之平均亮度間之平均亮度差，以判斷手指影像是否具有活體特徵。In one embodiment, the foregoing step of determining whether a finger image has a living body characteristic based on the average brightness of a finger image captured by the pixel sensing unit includes: determining whether the finger image has the average brightness difference between the average brightness of each finger image. Living characteristics.

一實施例中，根據各手指影像之平均亮度間之平均亮度差，以判斷手指影像是否具有活體特徵之步驟包括：以一個手指影像之平均亮度作為第一比較基準，將這個手指影像後續的至少一個手指影像之平均亮度與第一比較基準比較，得到一差值，並判斷此差值是否超過一平均差門檻值；之後，再以另一個手指影像之平均亮度作為第二比較基準，將這另一個手指影像後續的至少一個手指影像之平均亮度與第二比較基準比較，得到另一差值，並判斷此另一差值是否超過平均差門檻值；以及當差值超過平均差門檻值之累計次數超過一次數門檻值時，判斷為具有活體特徵。In an embodiment, the step of determining whether a finger image has a living feature according to the average brightness difference between the average brightness of each finger image includes: using the average brightness of a finger image as a first comparison reference, The average brightness of one finger image is compared with the first comparison reference to obtain a difference value, and it is determined whether the difference value exceeds an average difference threshold value. After that, the average brightness of the other finger image is used as the second comparison reference. The average brightness of at least one subsequent finger image of the other finger image is compared with the second comparison reference to obtain another difference value, and determine whether the other difference value exceeds the average difference threshold value; and when the difference value exceeds the average difference threshold value, When the accumulated number of times exceeds the threshold of one number of times, it is judged that it has living characteristics.

一實施例中，手指影像包含依序擷取之一第一手指影像、一第二手指影像、一第一亮度比較組、以及一第二亮度比較組，其中，第一亮度比較組包含從第一手指影像開始之多個手指影像，第二亮度比較組包含第二手指影像與其後之至少一個手指影像，第一亮度比較組不包含此至少一個手指影像，第一亮度比較組的多個手指影像中包含第二手指影像，前述之根據手指影像之平均亮度間之平均亮度差，以判斷手指影像是否具有活體特徵之步驟包含：擷取各手指影像之平均亮度；將第一亮度比較組中手指影像之平均亮度，分別與第一手指影像之平均亮度比較，以分別產生第一亮度比較組中各手指影像之平均亮度差；將第二亮度比較組中至少一手指影像之平均亮度，與第二手指影像比較，以產生第二亮度比較組中至少一手指影像之平均亮度差；設定一平均差門檻值，根據第一、二亮度比較組中各手指影像之平均亮度差，累計手指影像之平均亮度差中超過平均差門檻值之次數；以及設定一次數門檻值，當次數高於次數門檻值，判斷手指影像具有活體特徵。In one embodiment, the finger image includes a first finger image, a second finger image, a first brightness comparison group, and a second brightness comparison group, which are sequentially captured. The first brightness comparison group includes the first brightness comparison group. A plurality of finger images starting from a finger image, the second brightness comparison group includes the second finger image and at least one finger image thereafter, the first brightness comparison group does not include the at least one finger image, and the plurality of fingers of the first brightness comparison group The image includes a second finger image, and the aforementioned step of determining whether the finger image has a living feature based on the average brightness difference between the average brightness of the finger image includes: capturing the average brightness of each finger image; comparing the first brightness in the group The average brightness of the finger image is compared with the average brightness of the first finger image to generate the average brightness difference of each finger image in the first brightness comparison group; the average brightness of at least one finger image in the second brightness comparison group is compared with Compare the second finger images to generate the average brightness difference of at least one finger image in the second brightness comparison group; set an average Threshold value, based on the average brightness difference of each finger image in the first and second brightness comparison groups, accumulating the number of times that the average brightness difference of the finger image exceeds the average difference threshold value; and setting a one-time threshold value, when the number is higher than the number threshold value , Judge that the finger image has living characteristics.

一實施例中，平均差門檻值可依據一使用者之一呼吸特徵、或一心跳特徵而決定。In one embodiment, the average difference threshold value may be determined according to a breathing characteristic or a heartbeat characteristic of a user.

一實施例中，手指之識別資訊，包含手指之指紋特徵或運動軌跡。In one embodiment, the finger identification information includes fingerprint characteristics or motion trajectories of the fingers.

有關本發明之前述及其他技術內容、特點與功效，在以下配合參考圖式之一較佳實施例的詳細說明中，將可清楚的呈現。以下實施例中所提到的方向用語，例如：上、下、左、右、前或後等，僅是參考附加圖式的方向。本發明中的圖式均屬示意，主要意在表示各裝置以及各元件間之功能作用關係，至於形狀、厚度與寬度則並未依照比例繪製。The foregoing and other technical contents, features, and effects of the present invention will be clearly presented in the following detailed description of a preferred embodiment with reference to the accompanying drawings. The directional terms mentioned in the following embodiments, such as: up, down, left, right, front, or rear, are only directions referring to the attached drawings. The drawings in the present invention are schematic, and are mainly intended to represent the functional relationship between each device and each component. As for the shape, thickness, and width, they are not drawn to scale.

參照第1圖，其中顯示根據本發明一個觀點之光學識別方法之流程圖。根據圖式，本發明之光學識別方法，其包含：投射光至一手指以產生一反射光(S1)；以一像素感測單元，接收反射光以產生多個手指影像 (S2)；計算擷取手指影像的所需曝光時間或平均亮度 (S3)；以及根據像素感測單元擷取手指影像的所需曝光時間或平均亮度，判斷手指影像是否具有一活體特徵 (S4)；其中，當手指影像具有活體特徵時，則根據手指影像產生識別資訊； (S5)；或者當手指影像不具有活體特徵時，或者當手指影像不具有活體特徵時，則不根據手指影像產生識別資訊，且像素感測單元可(optionally)停止產生後續手指影像(可停止亦可不停止) (S6)。Referring to FIG. 1, there is shown a flowchart of an optical identification method according to an aspect of the present invention. According to the figure, the optical recognition method of the present invention includes: projecting light onto a finger to generate a reflected light (S1); using a pixel sensing unit to receive the reflected light to generate a plurality of finger images (S2); Taking the required exposure time or average brightness of the finger image (S3); and determining whether the finger image has a living feature according to the required exposure time or average brightness of the finger image captured by the pixel sensing unit (S4); When the image has living features, identification information is generated based on the finger image; (S5); or when the finger image does not have living characteristics, or when the finger image does not have living characteristics, the identification information is not generated based on the finger image, and the pixel sense The measuring unit may (optionally) stop generating subsequent finger images (can or may not stop) (S6).

關於本發明所提供之光學識別方法之步驟S1、S2、S5、S6，第2圖顯示對應此些步驟之手指影像感測器之一設計實施例，其中顯示光源提供光線投射至手指，光線投射至手指後產生反射光、像素感測單元接收反射光以產生多個手指影像(及/或多個後續手指影像)，以供判斷活體特徵以及識別資訊。重要地，無論判斷活體特徵、或判斷識別資訊，皆可藉由圖2中同一光源與同一像素感測單元所擷取的手指影像來達成。先前技術之光學識別系統難以辨別指紋是否為仿製，而先前技術之電容式感測器，僅能判斷碰觸物之運動，也無法判斷碰觸物是否為活體手指。相較於先前技術，本發明根據像素感測單元擷取手指影像的所需曝光時間或平均亮度，以判斷手指影像是否具有一活體特徵，可以提高防偽功能，而且判斷活體特徵與判斷識別資訊，皆可藉由本發明之同一光源與同一像素感測單元所產生，其詳述如後。Regarding steps S1, S2, S5, and S6 of the optical recognition method provided by the present invention, FIG. 2 shows a design example of a finger image sensor corresponding to these steps, in which a display light source provides light projection to a finger, and light projection Reflected light is generated after reaching the finger, and the pixel sensing unit receives the reflected light to generate multiple finger images (and / or multiple subsequent finger images) for determining living body characteristics and identification information. Importantly, regardless of the characteristics of the living body or the identification information, it can be achieved by the finger images captured by the same light source and the same pixel sensing unit in FIG. 2. The optical recognition system of the prior art is difficult to distinguish whether the fingerprint is imitation, and the capacitive sensor of the prior art can only judge the movement of the touching object, and it is also impossible to determine whether the touching object is a living finger. Compared with the prior art, the present invention determines whether the finger image has a living body feature according to the required exposure time or average brightness of the finger image captured by the pixel sensing unit, which can improve the anti-counterfeiting function, and determine the living body feature and identification information. Both can be generated by the same light source and the same pixel sensing unit of the present invention, which will be described in detail later.

前述各手指影像之平均亮度，例如可為各手指影像中全部像素之平均亮度，即[手指影像之平均亮度為(手指影像中全部像素之亮度相加值)除以(手指影像中全部像素之數量)]，或是，也可以僅選取各手指影像中之部分像素加以平均，例如，可以將過亮或過暗的像素去除、或是將邊緣的像素去除，等等。例如，當一像素之亮度介於0與255之間，圖3中，第一手指影像之平均亮度為100，到第二手指影像之平均亮度成為105，代表擷取之手指影像之平均亮度，為接近中間亮度之範圍(接近0與255之中間)，且手指影像之平均亮度在逐漸增加中。The average brightness of each finger image may be, for example, the average brightness of all pixels in each finger image, that is, [the average brightness of the finger image is (the sum of the brightness of all pixels in the finger image) divided by (the sum of all pixels in the finger image) (Quantity)], or you can select only some pixels in each finger image and average them, for example, you can remove pixels that are too bright or too dark, or remove pixels at the edges, and so on. For example, when the brightness of a pixel is between 0 and 255, in FIG. 3, the average brightness of the first finger image is 100, and the average brightness of the second finger image is 105, which represents the average brightness of the captured finger image. It is close to the middle brightness range (close to the middle of 0 and 255), and the average brightness of the finger image is gradually increasing.

根據本發明，當進行判斷手指影像是否包含活體特徵之步驟時，若手指移動，則產生之手指影像，可能會造成誤判。一實施例中，光學識別方法又包含：判斷像素感測單元擷取之手指影像，是否具有一運動狀態，當手指影像具有運動狀態時，則像素感測單元停止產生手指影像。According to the present invention, when the step of determining whether the finger image includes a living body feature, if the finger moves, the generated finger image may cause a misjudgment. In an embodiment, the optical recognition method further includes: determining whether the finger image captured by the pixel sensing unit has a motion state, and when the finger image has a motion state, the pixel sensing unit stops generating a finger image.

像素感測單元具有一感測動態範圍，為使產生之手指影像之像素能對應於此感測動態範圍中，須根據此感測動態範圍而決定各手指影像之所需曝光時間。例如反射效果較差之物件，其所需曝光時間較長；反射效果較佳之物件，其所需曝光時間較短。一般仿製手指(或仿製指紋)之反射效果，會與活體手指不同，代表根據同一感測動態範圍下，擷取仿製手指(或仿製指紋) 之手指影像所需曝光時間範圍，不同於具有活體特徵之手指影像所需曝光時間範圍。The pixel sensing unit has a sensing dynamic range. In order for the pixels of the generated finger image to correspond to the sensing dynamic range, the required exposure time of each finger image must be determined according to the sensing dynamic range. For example, an object with a poor reflection effect requires a longer exposure time; an object with a better reflection effect requires a shorter exposure time. Generally, the reflection effect of the imitation finger (or imitation fingerprint) will be different from that of the living finger, which represents the exposure time range required to capture the finger image of the imitation finger (or imitation fingerprint) under the same sensing dynamic range, which is different from the characteristics of the living body Finger finger image exposure time range.

一實施例中，活體特徵可根據一曝光時間門檻值來判斷。此曝光時間門檻值，可僅設上限、僅設下限、或上下限皆設。例如：根據具有活體特徵之手指影像所需曝光時間中最長者而決定曝光時間上限門檻值，即高於曝光時間上限門檻值之手指影像，不具有活體特徵，短於曝光時間上限門檻值之手指影像，具有活體特徵；或根據具有活體特徵之手指影像所需曝光時間中最短者而決定曝光時間下限門檻值；或根據具有活體特徵之手指影像所需曝光時間中最長者及最短者而決定曝光時間上下限門檻值。前述之根據像素感測單元擷取手指影像的所需曝光時間，判斷手指影像是否具有活體特徵之步驟可包含：當各手指影像之所需曝光時間低於曝光時間上限門檻值，判斷手指影像具有活體特徵，反之則判斷手指影像不具有活體特徵；或當各手指影像之所需曝光時間高於曝光時間下限門檻值，判斷手指影像具有活體特徵，反之則判斷手指影像不具有活體特徵；或當各手指影像之所需曝光時間落於曝光時間上下限門檻值之間，判斷手指影像具有活體特徵，反之則判斷手指影像不具有活體特徵。In one embodiment, the characteristics of the living body can be determined according to an exposure time threshold. This exposure time threshold can be set only for the upper limit, only the lower limit, or both. For example, the maximum exposure time threshold is determined based on the longest exposure time of a finger image with living characteristics, that is, a finger image that is higher than the upper exposure time threshold does not have a living feature and is shorter than the upper exposure time threshold. Image with living characteristics; or determine the lower exposure threshold based on the shortest exposure time required for finger images with living characteristics; or determine the exposure based on the longest and shortest exposure time for finger images with living characteristics Time threshold. The foregoing step of judging whether a finger image has a living feature according to the required exposure time of a finger image captured by the pixel sensing unit may include: when the required exposure time of each finger image is lower than the upper limit of the exposure time, determining whether the finger image has Living characteristics, on the contrary, it is judged that the finger image does not have living characteristics; or when the required exposure time of each finger image is higher than the lower exposure time threshold, it is judged that the finger image has living characteristics, otherwise it is judged that the finger image does not have living characteristics; or when The required exposure time for each finger image falls between the upper and lower thresholds of the exposure time to determine that the finger image has living characteristics, otherwise it is determined that the finger image does not have living characteristics.

同樣地，當像素感測單元具有一感測曝光時間，手指影像之像素對應於此感測動態範圍，會有不同之平均亮度。例如反射效果較差之物件，其平均亮度較低；反射效果較佳之物件，其平均亮度較高。一般仿製手指(或仿製指紋)之光反射效果，會與活體手指不同，代表根據同一感測曝光時間下，擷取仿製手指(或仿製指紋) 之手指影像之平均亮度範圍，不同於具有活體特徵之手指影像之平均亮度範圍。Similarly, when the pixel sensing unit has a sensing exposure time, the pixels of the finger image correspond to the sensing dynamic range and have different average brightness. For example, objects with poor reflection effects have lower average brightness; objects with better reflection effects have higher average brightness. The light reflection effect of a generic finger (or fingerprint) is different from that of a living finger, which represents the average brightness range of a finger image captured from a fake finger (or fingerprint) under the same sensing exposure time. The average brightness range of the finger image.

一實施例中，活體特徵可根據一亮度門檻值來判斷，此亮度門檻值，可僅設上限、僅設下限、或上下限皆設。例如：根據具有活體特徵之手指影像中平均亮度最低者而決定亮度下限門檻值，即低於亮度下限門檻值之手指影像，不具有活體特徵，高於亮度下限門檻值之手指影像，具有活體特徵；或根據具有活體特徵之手指影像中平均亮度最高者而決定亮度上限門檻值；根據具有活體特徵之手指影像中平均亮度最高與最低者而決定亮度上下限門檻值。前述之根據像素感測單元擷取手指影像的平均亮度，判斷手指影像是否具有一活體特徵之步驟包含：當手指影像的平均亮度高於亮度下限門檻值，判斷手指影像具有活體特徵，反之則判斷手指影像不具有活體特徵；或當手指影像的平均亮度低於亮度上限門檻值，判斷手指影像具有活體特徵，反之則判斷手指影像不具有活體特徵；或當手指影像的平均亮度落於亮度上下限門檻值之間，判斷手指影像具有活體特徵，反之則判斷手指影像不具有活體特徵。In one embodiment, the characteristics of the living body can be determined according to a brightness threshold. The brightness threshold can be set to only an upper limit, only a lower limit, or both. For example, the lower brightness threshold is determined according to the lowest average brightness of the finger images with living characteristics. That is, the finger images below the lower brightness threshold have no living characteristics, and the finger images above the lower brightness threshold have living characteristics. ; Or determine the upper brightness threshold based on the highest average brightness in a finger image with living features; determine the upper and lower brightness threshold based on the highest and lowest average brightness in a finger image with living features. The foregoing step of determining whether a finger image has a living feature according to the average brightness of the finger image captured by the pixel sensing unit includes: when the average brightness of the finger image is higher than the lower brightness threshold, determining that the finger image has a living feature; otherwise, determining The finger image does not have living characteristics; or when the average brightness of the finger image is lower than the upper limit of the brightness, it is judged that the finger image has living characteristics, otherwise it is judged that the finger image does not have living characteristics; or when the average brightness of the finger image falls below the brightness upper and lower limits Between the threshold values, it is judged that the finger image has living characteristics, otherwise it is judged that the finger image does not have living characteristics.

前述之手指影像的平均亮度，可為依據多個手指影像的平均亮度，或各別的手指影像的單獨平均亮度。使用者可依需要決定平均亮度之決定方式，例如當感測曝光時間較短時，擷取多個手指影像的平均亮度；或感測曝光時間較長時，擷取各手指影像的單獨平均亮度等。The average brightness of the aforementioned finger images may be based on the average brightness of a plurality of finger images or the individual average brightness of each finger image. Users can determine the average brightness according to their needs. For example, when the sensing exposure time is short, the average brightness of multiple finger images is captured; or when the sensing exposure time is long, the individual average brightness of each finger image is captured. Wait.

手指影像所具有之活體特徵，在另一實施例中，可根據多個手指影像的平均亮度變化來判斷，此變化例如是因為呼吸、心跳、或其他活體生命跡象而產生，以致於手指影像中，具有平均亮度變化。一實施例中，前述之根據像素感測單元擷取手指影像的平均亮度，判斷手指影像是否具有活體特徵之步驟包含：根據各手指影像之平均亮度間之平均亮度差，以判斷手指影像是否具有活體特徵。In another embodiment, the characteristics of the living body of the finger image can be determined according to the average brightness change of multiple finger images. This change is caused by, for example, breathing, heartbeat, or other signs of life in the finger image. , With average brightness change. In one embodiment, the foregoing step of determining whether a finger image has a living body characteristic based on the average brightness of a finger image captured by the pixel sensing unit includes: determining whether the finger image has the average brightness difference between the average brightness of each finger image. Living characteristics.

根據各手指影像之平均亮度間之平均亮度差來判斷活體特徵，有許多實施方式，圖3顯示本發明之一實施例，其詳述如下：手指影像包含依序擷取之一第一手指影像、一第二手指影像、一第一亮度比較組、以及一第二亮度比較組。第一亮度比較組包含從第一手指影像開始之多個手指影像，第二亮度比較組包含第二手指影像與其後之至少一個手指影像（圖3中以第八手指影像為例）。第一亮度比較組不包含此至少一個手指影像（圖3中，第一亮度比較組不包含第八手指影像為例），第一亮度比較組的多個手指影像中包含第二手指影像。There are many embodiments for judging the characteristics of a living body based on the average brightness difference between the average brightness of each finger image. FIG. 3 shows an embodiment of the present invention, which is detailed as follows: The finger image includes one first finger image sequentially captured. , A second finger image, a first brightness comparison group, and a second brightness comparison group. The first brightness comparison group includes a plurality of finger images starting from the first finger image, and the second brightness comparison group includes a second finger image and at least one finger image subsequent thereto (the eighth finger image is taken as an example in FIG. 3). The first brightness comparison group does not include the at least one finger image (in FIG. 3, the first brightness comparison group does not include the eighth finger image as an example), and the multiple finger images of the first brightness comparison group include the second finger image.

前述之根據手指影像之平均亮度間之平均亮度差，以判斷手指影像是否具有活體特徵之步驟包含：擷取各手指影像之平均亮度；將第一亮度比較組中各手指影像之平均亮度，分別與第一手指影像之平均亮度比較(第二手指影像之平均亮度減第一手指影像之平均亮度、第三手指影像之平均亮度減第一手指影像之平均亮度…)，以分別產生第一亮度比較組中各手指影像之平均亮度差(顯示於圖式中平均亮度差5、15…)；將第二亮度比較組中至少一手指影像之平均亮度(此實施例中，以第八手指影像之平均亮度為例)，與第二手指影像比較，以產生第二亮度比較組中至少一個手指影像之平均亮度差(顯示於圖3，第八手指影像之平均亮度差為25)；設定一平均差門檻值(圖式中，以15為例，然實施時不限於15，可依需要而定)，根據第一、二亮度比較組中各手指影像之平均亮度差，累計手指影像之平均亮度差中超過平均差門檻值之次數；以及設定一次數門檻值(圖式中，以6次為例，然實施時不限於15，可依需要而定)，當次數高於次數門檻值，判斷手指影像具有活體特徵。The aforementioned steps for determining whether a finger image has a living feature based on the average brightness difference between the average brightness of the finger images include: capturing the average brightness of each finger image; comparing the average brightness of each finger image in the first brightness group, respectively Compare with the average brightness of the first finger image (average brightness of the second finger image minus the average brightness of the first finger image, average brightness of the third finger image minus the average brightness of the first finger image ...) to generate the first brightness respectively Compare the average brightness difference of each finger image in the comparison group (shown in the figure as the average brightness difference of 5, 15 ...); compare the average brightness of at least one finger image in the second brightness group (in this embodiment, use the eighth finger image Take the average brightness as an example) to compare with the second finger image to generate the average brightness difference of at least one finger image in the second brightness comparison group (shown in FIG. 3, the average brightness difference of the eighth finger image is 25); set a Average difference threshold (15 is used as an example in the figure, but it is not limited to 15 during implementation, and can be determined as needed), according to the level of each finger image in the first and second brightness comparison groups Brightness difference, the number of times that the average brightness difference of the finger image has exceeded the average difference threshold; and a threshold is set once (in the figure, 6 times are taken as an example, but the implementation is not limited to 15, and can be determined as needed), When the number of times is higher than the number of times threshold, it is judged that the finger image has living characteristics.

上述之平均差門檻值，在一實施例中，例如但不限於可為一絕對值，即，若在後之手指影像之平均亮度低於在先手指影像之平均亮度，而差值高於此絕對值時，亦可計算次數。The above average difference threshold value may be an absolute value, for example, but not limited to, in an embodiment, that is, if the average brightness of the finger image in the following is lower than the average brightness of the previous finger image, and the difference is higher than this For absolute values, counts can also be calculated.

使用者也可根據本發明所提供之技術特徵，修正部分實施內容，以達成判斷活體特徵之功效。例如，前述之累計手指影像之平均亮度差超過平均差門檻值之次數，高於次數門檻值時，判斷手指影像具有活體特徵之步驟，也可思及以下之應用：當判斷手指影像之平均亮度差超過平均差門檻值之次數，超過另一次數門檻值時，判斷手指影像中不包含活體特徵。此外，當手指影像中沒有活體特徵，可限制判斷手指影像之次數，持續地判斷將浪費計算資源與時間。The user can also modify some of the implementation contents according to the technical features provided by the present invention to achieve the effect of judging the characteristics of the living body. For example, the number of times that the average brightness difference of the accumulated finger image exceeds the average difference threshold, and when the number threshold is higher, the step of judging that the finger image has living characteristics can also consider the following applications: When judging the average brightness of the finger image The number of times the difference exceeds the average difference threshold, and when the threshold is exceeded for another number of times, it is determined that the finger image does not include a living feature. In addition, when there is no living body feature in the finger image, the number of judgments of the finger image can be limited, and continuous judgment will waste computing resources and time.

根據圖3，第一亮度比較組與第二亮度比較組所包含之手指影像之數量不同。然而，若有需要，第一亮度比較組與第二亮度比較組所包含之手指影像之數量也可相同，例如第一亮度比較組包含四個手指影像，第二亮度比較組包含四個手指影像。因此，第一亮度比較組與第二亮度比較組所包含之手指影像之數量不限於圖式中所顯示。According to FIG. 3, the number of finger images included in the first brightness comparison group and the second brightness comparison group are different. However, if necessary, the number of finger images included in the first brightness comparison group and the second brightness comparison group may be the same. For example, the first brightness comparison group contains four finger images, and the second brightness comparison group contains four finger images. . Therefore, the number of finger images included in the first brightness comparison group and the second brightness comparison group is not limited to that shown in the drawings.

一實施例中，平均差門檻值可依據一使用者之一呼吸特徵、或一心跳特徵而決定。例如，當依據呼吸特徵而定時，因呼吸之頻率較低，平均亮度差變化較緩，故平均差門檻值可設一較低值。又例如，當依據心跳特徵而定時，因心跳之頻率較呼吸之頻率高，平均亮度差變化相對較大，故平均差門檻值可設一較高值（相對於呼吸特徵而言）。In one embodiment, the average difference threshold value may be determined according to a breathing characteristic or a heartbeat characteristic of a user. For example, when timing is based on breathing characteristics, the average brightness difference changes slowly because the frequency of breathing is low, so the average difference threshold can be set to a lower value. For another example, when timing is based on the characteristics of the heartbeat, because the frequency of the heartbeat is higher than the frequency of breathing, the average brightness difference changes relatively, so the average difference threshold value can be set to a higher value (relative to the breathing characteristics).

此外，平均差門檻值也可依據擷取手指影像之頻率而定。例如，當擷取手指影像之頻率較低時，因手指影像間隔時間較長，其平均亮度差變化較高，故平均差門檻值可設一較高值。又例如，當擷取手指影像之頻率較高時，手指影像間隔時間較短，其平均亮度差變化較低，故平均差門檻值可設一較低值。In addition, the average difference threshold can also be determined based on the frequency of capturing finger images. For example, when the frequency of capturing a finger image is low, the average brightness difference of a finger image is relatively high due to the long interval between finger images, so the average difference threshold can be set to a higher value. For another example, when the frequency of capturing a finger image is high, the interval between finger images is short, and the average brightness difference change is low. Therefore, the average difference threshold can be set to a lower value.

一實施例中，前述之次數門檻值，可依據擷取手指影像之頻率而定。例如，當擷取手指影像之頻率較低時，因手指影像間之時間間隔較長，故次數門檻值設一較低值，使擷取之平均亮度差可判斷是否具有活體特徵。又例如，當擷取手指影像之頻率較高時，因手指影像間之時間間隔較短，故次數門檻值設一較高值，使擷取之平均亮度差可判斷是否具有活體特徵。In one embodiment, the aforementioned threshold of number of times may be determined according to the frequency of capturing a finger image. For example, when the frequency of capturing finger images is low, because the time interval between finger images is long, the threshold of the number of times is set to a low value, so that the average brightness difference of the captured images can determine whether it has a living body feature. For another example, when the frequency of capturing finger images is high, because the time interval between finger images is short, the threshold value of the number is set to a high value, so that the average brightness difference captured can determine whether it has a living body feature.

以上根據圖3所述之實施方式，僅是舉例說明本發明其中一種較佳方式，但並非唯一實施方式。如前所述，本發明可使用多種方式來判斷活體特徵，例如但不限於可根據曝光時間門檻值來判斷活體特徵、可根據亮度門檻值來判斷活體特徵、或者可根據各手指影像之平均亮度間之平均亮度差來判斷活體特徵。而就「根據平均亮度差來判斷活體特徵」而言，圖3所述之方式重點在於計算平均亮度間之平均亮度差，並適時更新比較基準。也就是說，先以一個手指影像之平均亮度作為比較基準（第一比較基準），將後續其他手指影像之平均亮度與第一比較基準比較；之後，可根據擷取手指影像之頻率、及／或根據欲判斷的活體特徵，而再以一個手指影像之平均亮度作為比較基準（第一比較基準），將後續其他手指影像之平均亮度與第一比較基準比較；依此類推，而當差值超過平均差門檻值之次數超過次數門檻值時，即判斷為具有活體特徵。本領域內的技術人士可以根據本發明，而思及各種變化，例如，圖3所述之方式中，在以第一手指影像之平均亮度作為比較基準之後，不必須以第二手指影像之平均亮度來更新作為比較基準，而例如可以以第三指影像之平均亮度作為比較基準（即，將第八手指影像之平均亮度差與第三手指影像之平均亮度差比較，而不是與第二手指影像之平均亮度差比較），等等。The above embodiment according to FIG. 3 is merely an example for illustrating one of the preferred modes of the present invention, but it is not the only embodiment. As mentioned above, the present invention can use various methods to determine the characteristics of the living body, such as, but not limited to, the characteristics of the living body can be determined according to the exposure time threshold, the characteristics of the living body can be determined according to the brightness threshold, or the average brightness of each finger image can be determined The average brightness difference between the two is used to judge the characteristics of the living body. As far as "determining the characteristics of a living body based on the average brightness difference", the method described in FIG. 3 focuses on calculating the average brightness difference between the average brightness and updating the comparison benchmark in a timely manner. In other words, the average brightness of one finger image is used as a comparison reference (the first comparison reference), and the average brightness of other subsequent finger images is compared with the first comparison reference; after that, the frequency of the captured finger image and / Or according to the characteristics of the living body to be judged, and then use the average brightness of one finger image as a comparison reference (the first comparison reference), compare the average brightness of subsequent subsequent finger images with the first comparison reference; and so on, and the difference When the number of times exceeding the average difference threshold exceeds the number of thresholds, it is judged to have living characteristics. Those skilled in the art can consider various changes according to the present invention. For example, in the manner described in FIG. 3, after using the average brightness of the first finger image as a reference, it is not necessary to use the average of the second finger image. The brightness is updated as a comparison reference, and for example, the average brightness of the third finger image may be used as a comparison reference (that is, the average brightness difference of the eighth finger image is compared with the average brightness difference of the third finger image, rather than the second finger image Image average brightness difference), and so on.

一實施例中，手指之識別資訊，包含手指之指紋特徵或運動軌跡。In one embodiment, the finger identification information includes fingerprint characteristics or motion trajectories of the fingers.

以上已針對較佳實施例來說明本發明，唯以上所述者，僅係為使熟悉本技術者易於了解本發明的內容而已，並非用來限定本發明之權利範圍。在本發明之相同精神下，熟悉本技術者可以思及各種等效變化。各實施例中圖示直接連接的兩電路或元件間，可插置不影響主要功能的其他電路或元件，僅需對應修改相關電路或是訊號的意義即可。凡此種種，皆可根據本發明的教示類推而得，因此，本發明的範圍應涵蓋上述及其他所有等效變化。前述之各個實施例，並不限於單獨應用，亦可以組合應用，例如但不限於將兩實施例併用，或是以其中一個實施例的局部電路代換另一實施例的對應電路。The present invention has been described above with reference to the preferred embodiments, but the above is only for making those skilled in the art easily understand the content of the present invention, and is not intended to limit the scope of rights of the present invention. In the same spirit of the invention, those skilled in the art can think of various equivalent changes. In the embodiments, two circuits or components that are directly connected as shown in the figure can be inserted with other circuits or components that do not affect the main function, and only need to correspondingly modify the meaning of the related circuits or signals. All these can be deduced by analogy according to the teachings of the present invention. Therefore, the scope of the present invention should cover the above and all other equivalent changes. Each of the foregoing embodiments is not limited to a single application, and may also be applied in combination, such as, but not limited to, combining the two embodiments, or substituting a local circuit of one embodiment for a corresponding circuit of another embodiment.

步驟 S1~S6Steps S1 ~ S6

［第1圖］顯示根據本發明一實施例之光學識別方法之流程圖； ［第2圖］顯示根據本發明一實施例之手指影像感測設計之示意圖； ［第3圖］顯示根據本發明一實施例之判斷活體特徵之示意圖。[Fig. 1] shows a flowchart of an optical recognition method according to an embodiment of the present invention; [Fig. 2] shows a schematic diagram of a finger image sensing design according to an embodiment of the present invention; [Fig. 3] shows according to the present invention A schematic diagram of judging the characteristics of a living body according to an embodiment.

Claims (7)

一種光學識別方法，其包含：投射光至一手指以產生一反射光；以一像素感測單元，接收該反射光以產生多個手指影像；以及根據該像素感測單元擷取該些手指影像的平均亮度間之平均亮度差，判斷該些手指影像是否具有一活體特徵；其中，當該手指影像具有該活體特徵時，則根據手指影像產生識別資訊；或者當該手指影像不具有該活體特徵時，則不根據手指影像產生識別資訊。An optical recognition method includes: projecting light onto a finger to generate a reflected light; using a pixel sensing unit to receive the reflected light to generate a plurality of finger images; and capturing the finger images according to the pixel sensing unit The average brightness difference between the average brightness of the finger to determine whether the finger images have a living feature; wherein when the finger image has the living feature, identification information is generated based on the finger image; or when the finger image does not have the living feature , No identification information is generated based on the finger image. 如申請專利範圍第1項所述之光學識別方法，又包含：當該手指影像不具有該活體特徵時，該像素感測單元停止產生該些後續手指影像。According to the optical identification method described in the first item of the patent application scope, the method further includes: when the finger image does not have the living body feature, the pixel sensing unit stops generating the subsequent finger images. 如申請專利範圍第1項所述之光學識別方法，又包含：判斷該像素感測單元擷取之該些手指影像，是否具有一運動狀態，其中當該些手指影像具有該運動狀態時，該像素感測單元停止產生該些手指影像。According to the optical identification method described in item 1 of the scope of patent application, the method further comprises: judging whether the finger images captured by the pixel sensing unit have a motion state, and when the finger images have the motion state, the The pixel sensing unit stops generating the finger images. 如申請專利範圍第1項所述之光學識別方法，其中根據各該手指影像之該平均亮度間之平均亮度差，以判斷該些手指影像是否具有該活體特徵之步驟包括：以一個手指影像之平均亮度作為第一比較基準，將這個手指影像後續的至少一個手指影像之平均亮度與該第一比較基準比較，得到一差值，並判斷此差值是否超過一平均差門檻值；之後，再以另一個手指影像之平均亮度作為第二比較基準，將這另一個手指影像後續的至少一個手指影像之平均亮度與該第二比較基準比較，得到另一差值，並判斷此另一差值是否超過該平均差門檻值；以及當差值超過平均差門檻值之累計次數超過一次數門檻值時，判斷為具有活體特徵。The optical recognition method as described in the first item of the patent application scope, wherein the step of determining whether the finger images have the characteristics of the living body according to the average brightness difference between the average brightness of each finger image includes: The average brightness is used as a first comparison reference, and the average brightness of at least one subsequent finger image of the finger image is compared with the first comparison reference to obtain a difference value, and it is determined whether the difference value exceeds an average difference threshold value; Use the average brightness of the other finger image as a second comparison reference, compare the average brightness of at least one finger image subsequent to the other finger image with the second comparison reference to obtain another difference value, and determine the other difference value Whether the average difference threshold is exceeded; and when the cumulative number of times the difference exceeds the average difference threshold exceeds a threshold, it is judged to have a living body characteristic. 如申請專利範圍第1項所述之光學識別方法，其中該些手指影像包含依序擷取之一第一手指影像、一第二手指影像、一第一亮度比較組、以及一第二亮度比較組，其中，該第一亮度比較組包含從該第一手指影像開始之多個該手指影像，該第二亮度比較組包含該第二手指影像與其後之至少一該手指影像，該第一亮度比較組不包含此至少一該手指影像，該第一亮度比較組的多個該手指影像中包含該第二手指影像，前述之根據該些手指影像之該些平均亮度間之該平均亮度差，以判斷該些手指影像是否具有該活體特徵之步驟包含：擷取各該手指影像之該平均亮度；將該第一亮度比較組中各該手指影像之該平均亮度，分別與該第一手指影像之該平均亮度比較，以分別產生該第一亮度比較組中各該手指影像之該平均亮度差；將該第二亮度比較組中至少一該手指影像之該平均亮度，與第二手指影像比較，以產生該第二亮度比較組中至少一該手指影像之該平均亮度差；設定一平均差門檻值，根據該第一、二亮度比較組中各該手指影像之該平均亮度差，累計該些手指影像之該平均亮度差中超過該平均差門檻值之次數；以及設定一次數門檻值，當該次數高於該次數門檻值，判斷該手指影像具有該活體特徵。The optical recognition method according to item 1 of the scope of the patent application, wherein the finger images include a first finger image, a second finger image, a first brightness comparison group, and a second brightness comparison sequentially captured. Group, wherein the first brightness comparison group includes a plurality of the finger images starting from the first finger image, the second brightness comparison group includes the second finger image and at least one finger image subsequent thereto, the first brightness The comparison group does not include the at least one finger image, the plurality of the finger images in the first brightness comparison group include the second finger image, and the average brightness difference between the average brightnesses of the finger images according to the foregoing, The step of determining whether the finger images have the living feature includes: capturing the average brightness of each finger image; the average brightness of each finger image in the first brightness comparison group, and the first finger image respectively The average brightness comparison to generate the average brightness difference of each finger image in the first brightness comparison group; at least one finger shadow in the second brightness comparison group The average brightness of the image is compared with the second finger image to generate the average brightness difference of at least one of the finger images in the second brightness comparison group; an average difference threshold is set, and according to the first and second brightness comparison groups, The average brightness difference of each finger image, accumulating the number of times that the average brightness difference of the finger images exceeds the average difference threshold; and setting a number of thresholds, and when the number is higher than the number of thresholds, judging the finger The image has the characteristics of the living body. 如申請專利範圍第1項所述之光學識別方法，其中，該平均差門檻值可依據一使用者之一呼吸特徵、或一心跳特徵而決定。According to the optical identification method described in the first item of the patent application scope, wherein the average difference threshold value can be determined according to a breathing characteristic or a heartbeat characteristic of a user. 如申請專利範圍第1項所述之光學識別方法，其中，該手指之該識別資訊，包含該手指之指紋特徵或運動軌跡。The optical identification method according to item 1 of the scope of patent application, wherein the identification information of the finger includes fingerprint characteristics or motion trajectory of the finger.
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