KR101080645B1 - Rolling Fingerprint Acquiring Apparatus and Method - Google Patents

Abstract

A rotating fingerprint acquisition device and method thereof are disclosed. The rotating fingerprint obtaining apparatus of the present invention may acquire a rotating fingerprint including more fingerprint information than a planar fingerprint by analyzing a plurality of image frames generated by rotating contact with a fingerprint input window. The rotation fingerprint obtaining apparatus of the present invention uses an adaptive pyramid template projection method to synthesize a fingerprint image included in each frame into one rotation fingerprint.

Description

Rotating fingerprint acquisition device and method {Rolling Fingerprint Acquiring Apparatus and Method}

The present invention uses an adaptive pyramid template projection method that can synthesize a single rotation fingerprint according to an adaptive pyramid template projection method by analyzing a fingerprint image of a plurality of frames generated from a fingerprint in contact with a fingerprint input window. A rotating fingerprint acquisition device and method thereof are provided.

Biometric methods are widely used for authentication of individuals due to their uniqueness and high invariability. In this biometric method, fingerprint recognition is convenient and simple to use, making it the oldest and most generalized recognition method compared to other biometric fields.

In fact, fingerprint recognition devices are spreading to various fields that require authentication, such as access control, electronic commerce, financial transactions, security of personal computers (PCs), and office payment systems.

As a method of obtaining a fingerprint image, a method of obtaining only a flat fingerprint image by contacting only a central portion of the fingerprint with a fingerprint input window is currently widely used. This method is widely used because the image processing required for recognition is relatively simple, but has a disadvantage of weakening the recognition rate or imitation fingerprints due to the failure to secure the image of the entire fingerprint.

Another method is to obtain a rotating fingerprint. The method of acquiring a rotating fingerprint image is a method of acquiring a fingerprint image of the entire fingerprint portion by rotating a user's finger in contact with a fingerprint input window. Compared to the method of generating only the image of the center part, it can have an excellent recognition rate, but the image processing is relatively difficult and it is not widely used due to the fear of fingerprint loss in the image processing.

As a conventionally known method for obtaining a rotation fingerprint, there is a method (depending on the Republic of Korea Patent Publication No. 1997-0017033) depending on the hardware device, the method of calculating and matching the direction and feature points of the information input in time series for each frame. Patent No. 1999-013325).

An object of the present invention is to provide an adaptive pyramid template projection method that can synthesize a single rotation fingerprint according to an adaptive pyramid template projection method by analyzing a fingerprint image of a plurality of frames generated from a fingerprint in contact with a fingerprint input window. The present invention provides a rotating fingerprint acquisition device and a method thereof.

The rotation fingerprint acquisition method of the present invention for achieving the above object comprises the steps of acquiring a plurality of image frames from the fingerprint to rotate contact the fingerprint input window; Selecting a center frame F (c) located at the center of the plurality of image frames; Dividing a fingerprint data region from the image of the selected center frame F (c) and calculating a central coordinate on an x-axis of the divided fingerprint data region; And arranging the plurality of image frames in a pyramid form and superimposing them on the center coordinates of the center frame F (c) to obtain one rotation fingerprint.

The acquiring of the fingerprint may include extracting an image of a first size including the center x coordinate from the center frame F (c); Extracting an image from an F (c-k) frame and extracting an image from a left side of a coordinate from which the image is extracted from the F (c-k + 1) frame; Extracting an image from an F (c + k) frame and extracting an image from a right side of a coordinate from which the image is extracted from the F (c + k-1) frame; And forming the rotation fingerprint by adding the extracted images, wherein k is an integer satisfying 1 <k <K. Further, the K may vary depending on the size of the image frame.

The acquiring of the plurality of image frames may include: while the characteristic value of the image acquired through the fingerprint input window is out of a range of the reference characteristic value of the image when there is no fingerprint contact, the fingerprint input window. Can be obtained from

In accordance with another aspect of the present invention, there is provided a fingerprint fingerprint obtaining apparatus comprising: a fingerprint input unit configured to obtain a plurality of image frames from a fingerprint for rotating contact with a fingerprint input window; A center frame extractor which selects a center frame F (c) positioned at the center among the plurality of image frames; An object division processing unit for dividing a fingerprint data region from an image of the center frame F (c) selected by the center frame extraction unit; A center coordinate calculator configured to calculate a center coordinate on an x-axis of the fingerprint data area divided by the object division processor; And a rotation fingerprint registration unit configured to obtain one rotation fingerprint by arranging the plurality of image frames in a pyramid form and superimposing them on the center coordinates of the center frame F (c) extracted by the center coordinate calculation unit. .

The fingerprint acquisition device of the present invention may generate a rotation fingerprint from a fingerprint that is in rotational contact with a fingerprint input window. Rotating fingerprints are fingerprint data in a wider area than planar fingerprints, and more feature points can be extracted, thereby increasing the user authentication rate and significantly reducing the probability of authenticating the user differently.

The present invention significantly improves the image processing speed by reducing the image processing process for the entire number of the inputted image frames, thereby providing a very fast processing speed and being free from poor fingerprint characteristics.

1 is a block diagram of a fingerprint recognition device according to an embodiment of the present invention;
2 illustrates an example of a fingerprint image of a plurality of frames automatically stored by a time series scan method;
Figure 3 is a flow chart provided in the description of the rotation fingerprint generation process of the present invention,
4 is a diagram illustrating an example of an image of a fingerprint data region extracted from a central image frame;
FIG. 5 is an image of a morphological technique applied to the image of the fingerprint data region of FIG. 4; FIG.

BEST MODE FOR CARRYING OUT THE INVENTION The present invention will be described in more detail with reference to the drawings.

Referring to FIG. 1, the fingerprint acquisition apparatus 100 of the present invention includes a fingerprint input unit 110 and a fingerprint processing unit 130 to obtain a rotation fingerprint from a user fingerprint.

The fingerprint input unit 110 obtains a fingerprint image of a plurality of frames for obtaining a rotation fingerprint from a user fingerprint that is in contact with the fingerprint input window 111a and provides the fingerprint image to the fingerprint processor 130. Here, the rotating fingerprint (or rotating fingerprint image) is used in contrast to a flat fingerprint, and refers to a single fingerprint (image or image) obtained for the entire user fingerprint by rotating a round user's finger. Hereinafter, the rotating fingerprint, the rotating fingerprint image, the rotating fingerprint image are used in the same sense.

In detail, the fingerprint input unit 110 includes a fingerprint sensor 111, an image receiver 113, and a reception control unit 115. The fingerprint input unit 110 includes a user fingerprint that is rotated in contact with the fingerprint input window 111a of the fingerprint sensor 111. A fingerprint image of a plurality of frames is obtained according to a scan method.

The fingerprint sensor 111 obtains a fingerprint image of the fingerprint in contact with the fingerprint input window 111a and outputs the fingerprint image to the image receiver 113. The fingerprint sensor 111 may use a non-optical method, but an optical fingerprint sensor is preferable in consideration of formation of a fingerprint input window for rotation input of a fingerprint.

The image receiver 113 obtains a plurality of frames of fingerprint images from the fingerprint input unit 110 and outputs the fingerprint images to the fingerprint processor 130 under the control of the reception controller 115.

The reception controller 115 automatically detects whether a fingerprint is in contact with the fingerprint input window 111a based on an image input through the image receiver 113, and determines that the fingerprint is in contact with the fingerprint controller, thereby obtaining a plurality of rotation fingerprints. The image receiver 113 is controlled to generate an image of four frames.

For automatic detection, the reception controller 115 compares a characteristic value (eg, an average gradation value) of an image frame (background frame) when there is no fingerprint contact with a threshold value (or threshold range), and the image reception unit 113. If the characteristic value of the image input through the user is out of the threshold (or threshold range), it may be determined that there is a fingerprint contact.

The reception control unit 115 stores the image output from the fingerprint sensor 111 and provides the image processing unit 130 to the fingerprint processing unit 130 while the characteristic value of the image is out of the threshold (or threshold range). To control. Referring to FIG. 2, an example of a fingerprint image (1-frame to 8-frame) automatically stored in eight frames by a time series scan method is shown.

The fingerprint processor 130 receives a plurality of frames of fingerprint images generated according to a time series scan method from the image receiver 113 of the fingerprint input unit 110, and generates a single rotating fingerprint through an image processing process. When the rotation fingerprint generation process of the fingerprint processing unit 130 is outlined, a plurality of image frames received from the image receiving unit 113 based on a frame located in the center may be arranged as a pyramid template and projected while overlapping. Create a revolving fingerprint. To this end, the fingerprint processing unit 130 includes a central frame extracting unit 131, an object division processing unit 133, a central coordinate calculating unit 135, and a rotating fingerprint matching unit 137.

Hereinafter, referring to FIG. 3, operations of the center frame extractor 131, the object division processor 133, the center coordinate calculator 135, and the rotation fingerprint matcher 137 will be described.

Referring to FIG. 3, the fingerprint input unit 110 automatically recognizes a user fingerprint in contact with the fingerprint input window 111a to obtain a plurality of image frames, and extracts a central frame extracting unit 131 of the fingerprint processing unit 130. (S301, S303).

<Selection of center frame: S305>

The center frame extractor 131 receives a plurality of image frames through the fingerprint input unit 110 and estimates and selects the center frame based on Equation 1 below. Here, the "central frame" is an image frame located in the center among the image frames input through the fingerprint input unit 110, and is denoted as F (c).

Where F _C Is the number of the center frame, and n is the number of image frames received from the fingerprint input unit 110 (that is, n is an integer of n≥1).

As shown in FIG. 2, when eight video frames are input (n = 8), the fourth frame (4-frame) is selected as the center frame F (c).

<Separation of fingerprint data area: S307>

The object division processing unit 133 separates the background and the fingerprint data area from the center frame selected by the center frame extraction unit 131 by Equation 1, and extracts only the fingerprint data area.

In order to separate the fingerprint data area from the background, the object division processing unit 133 performs a subtraction operation between the reference background frame and the selected frame. Here, the reference background frame may be an image frame when the fingerprint image is not received and may use an image frame previously stored.

When the reference background frame is called B (x, y) and the selected center frame is m (x, y), the fingerprint data area R (x, y) is obtained as shown in Equation 2 below.

Referring to FIG. 4, the image 4c of the fingerprint data area obtained by subtracting each pixel value of the center frame 4b in the reference background frame 4a is shown.

<Calculation of center x coordinate of separated fingerprint data area: S309>

The central coordinate calculation unit 135 performs image processing on the resultant image processed by the object division processing unit 133 to obtain the center coordinates on the x-axis of the fingerprint data region extracted by the object division processing unit 133. Hereinafter, the center coordinate on the x axis of the fingerprint data area is simply referred to as 'center x coordinate'. The center x coordinate is a reference in the process of the rotation fingerprint matching unit 137 arranges and projects a plurality of image frames in a pyramid template.

First, the central coordinate calculation unit 135 performs a preprocessing process of integrating an image into one unit by applying a morphological technique (morphology technique, Morphology) to the image of the fingerprint data region from which the background is removed. Here, the morphological technique is a tool for extracting image elements that are useful for expressing or describing region shapes such as boundaries, skeletons, and blocks by manipulating morphological aspects of an image. Morphological techniques are used to clarify the intrinsic structure of an object after image preprocessing or initial object classification, or after such processing. In FIG. 5, an image 5a of the fingerprint data region and a resultant image 5b of which a morphological technique is applied and integrated into one unit are shown.

The center coordinate calculation unit 135 extracts an ellipse corresponding to the preprocessed fingerprint area, and then obtains a center x coordinate from the extracted ellipse. The height of the preprocessed image is the length of the longitudinal axis of the ellipse, and the width of the preprocessed image is the length of the horizontal axis of the ellipse. First, the central coordinate calculation unit 135 detects the outermost line of the preprocessed result image 5b and connects the horizontal lines, vertical lines, diagonal lines, etc. of the detected outermost line to represent an ellipse 5c-. Confirm 1).

The ellipse 5c-1 specified from the image to which the morphology technique is applied is not only close to the fingerprint form but also easy to calculate the center x coordinate. The inclination of the ellipse 5c-1 is preferably maintained at 90 ° to maintain the horizontal and vertical ratio.

The center coordinate calculation unit 135 generates a left vertical tangent 5c-2 and a right vertical tangent 5c-3 of the ellipse 5c-1, and calculates a center x coordinate using Equation 3 below.

Where X _M is the center x coordinate, X _L is the x-axis coordinate of the left vertical tangent 5c-2 of the ellipse 5c-1, and X _R is the right vertical tangent 5c-3 of the ellipse 5c-1. The x-axis coordinate of.

<Composite Rotation Fingerprint Projection by Adaptive Pyramid Template: S311>

The rotating fingerprint matching unit 137 projects a rotating fingerprint by applying a pyramid template, which is a pyramid-shaped projection window as shown in FIG. 6, to a plurality of image frames inputted through the fingerprint input unit 110. Create In other words, by applying a pyramid template to a plurality of image frames, only the necessary portions of each image frame are extracted and synthesized to generate a rotating fingerprint.

Referring to FIG. 6, the pyramid template includes a window for the center frame F (c) disposed on the top layer, and an F (ck) frame and an F (c + k) frame on the (k) th layer while lowering the layer. This is the structure where the window for is arranged. Therefore, the image of the center frame is extracted through the window of the uppermost layer, the image of the F (c-1) and F (c + 1) frames is extracted through the window of the first layer, and the image of the F through the window of the second layer. Images of (c-2) and F (c + 2) frames are extracted. 6 corresponds to the case of k = K. The width of the entire pyramid template is equal to the width of one image frame.

When the pyramid template of FIG. 6 is vertically projected, it may be displayed as shown in FIG. 7. At this time, the pyramid template is adaptively projected while moving as a whole according to the position of the center x coordinate and combined into one rotating fingerprint.

For example, referring to FIG. 8, a filter having a first window w1 having a center x coordinate in the center is applied to the center frame F (c), and a constant size is applied to the frame F (c-1). Apply a filter having a second window w2 positioned to the left of the first window w1, and having a constant size in the F (c + 1) frame and positioned to the right of the first window w1. Apply a filter with 3 windows (w3). In this form, a filter is applied to the F (ck) frame with the same size as the window applied to the F (c-k + 1) frame and to the left of the window, and to the F (c + k) frame. + k-1) Apply the filter with the same size as the window applied to the frame and the window to the right. The result of the adaptive projection according to the position of the center x coordinate will be one rotation fingerprint image frame as shown in FIG.

The rotation fingerprint synthesis process of FIGS. 6 to 8 corresponds to a process of extracting and synthesizing a required image portion from each of a plurality of image frames. Here, the image extracted from the center frame F (c) has a first size including a center x coordinate, and the images extracted from the F (ck) frame are each extracted from the F (c-k + 1) frame. The image extracted from the left side of the coordinates and extracted from the F (c + k) frame is extracted from the right side of the coordinates from which the image is extracted from the F (c + k-1) frame.

However, when the size of the image frame is 420 × 420, the width is 420 pixels (Pixel). If the size of the first window w1 is 80 pixels and the size of the remaining windows is 40 pixels, a total of 9 or more image frames are required. It is unknown whether the image input frame generated by the fingerprint input unit 110 may be 9 or more. However, even if a satisfactory number of image frames is obtained, the entire fingerprint frame may not be distributed because the area of the fingerprint is not distributed over the entire 420 pixels. There is no need.

Therefore, the total number of layers K of the pyramid template may be set according to the size of the fingerprint input window 111a. For example, since the larger the size of the input window is, the larger the size of the rotation fingerprint is, the total number of layers (K) of the pyramid template is preferably proportional to the size of the fingerprint input window 111a. An example of the number of (K) is shown.

Fingerprint input window size Total number of tiers in pyramid template (K) 160 × 120, 200 × 200 2 320 × 240, 420 × 420 3 680 × 480 5 1024 × 680 7

According to Table 1, when the size of the fingerprint input window 111a is 420 × 420, the number of layers of the pyramid template is 3, that is, K = 3. When K = 3, F (c-3), F (c-2), F (c-1), F (c), F (c + 1), F (c + 2), F (c + The seven frames of 3) are adaptively projected and matched to one rotating fingerprint. FIG. 8 corresponds to a case in which seven image frames are processed by applying three layers (K = 3) to a 420 × 420 image frame.

In this case, the window applied to the image frame of the last layer (K-th layer) may have a window size for projecting the entire area not projected in the previous layer. FIG. 8F shows an example with a 120 pixel window for F (c-3), and (g) shows an example with a 60 pixel window for F (c + 3).

Furthermore, for layers other than the uppermost layer and the lowermost layer (Kth layer), FIGS. 6 to 8 are shown and depicted as applying the same size window, but are not necessarily limited thereto. Depending on the arbitrary design or the location of the center x coordinate, the size of each layer may be designed differently.

9 (a) shows the rotation fingerprint generated by the rotation fingerprint matching unit 137 through the above process. It can be seen that the rotation fingerprint includes more fingerprint data information than the planar fingerprint shown in FIG. In addition, it can be seen that the rotation fingerprint generated using the pyramid template projection method generates the user's actual fingerprint without distortion such as ridge break or crushing of the image.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is clearly understood that the same is by way of illustration and example only and is not to be construed as limiting the scope of the invention as defined by the appended claims. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention.

Claims (8)

Obtaining a plurality of image frames from a fingerprint for rotating contact with the fingerprint input window;
Selecting a center frame F (c) located at the center of the plurality of image frames;
Dividing a fingerprint data region from the image of the selected center frame F (c) and calculating a central coordinate on an x-axis of the divided fingerprint data region; And
And obtaining one rotation fingerprint by applying a pyramid-shaped template to the plurality of image frames with respect to the center coordinates of the center frame F (c). Acquisition method.
The method of claim 1,
Acquiring the rotation fingerprint,
Extracting an image of a first size including the center x coordinate from the center frame F (c);
Extracting an image from an F (ck) frame, but extracting an image from a left side of a coordinate from which the image is extracted from the F (c-k + 1) frame;
Extracting an image from an F (c + k) frame and extracting an image from a right side of a coordinate from which the image is extracted from the F (c + k-1) frame; And
And adding the extracted images to form the rotation fingerprint,
And k is an integer satisfying 1 <k <K.
The method of claim 2,
The K is a rotation fingerprint acquisition method characterized in that the variable according to the size of the image frame.
The method of claim 1,
Acquiring the plurality of image frames,
And a characteristic value acquired from the fingerprint input window while the characteristic value of the image acquired through the fingerprint input window is outside the range of the reference characteristic value of the image when there is no fingerprint contact.
A fingerprint input unit configured to obtain a plurality of image frames from a fingerprint for rotating contact with the fingerprint input window;
A center frame extractor which selects a center frame F (c) positioned at the center among the plurality of image frames;
An object division processing unit for dividing a fingerprint data region from an image of the center frame F (c) selected by the center frame extraction unit;
A center coordinate calculator configured to calculate a center coordinate on an x-axis of the fingerprint data area divided by the object division processor; And
A rotation fingerprint registration unit which obtains one rotation fingerprint by applying a pyramid-shaped template to the plurality of image frames and projecting the center coordinates of the center frame F (c) extracted by the center coordinate calculation unit; Rotating fingerprint obtaining device comprising a.
The method of claim 5,
The rotation fingerprint matching unit synthesizes the rotation fingerprint by extracting images from the plurality of image frames,
In the center frame F (c), an image of the first size including the center x coordinate is extracted, and in the F (ck) frame, an image is extracted from the left side of the coordinate from which the image is extracted in the F (c-k + 1) frame. , In the F (c + k) frame, the image is extracted from the right side of the extracted coordinate in the F (c + k-1) frame.
And k is an integer satisfying 1 <k <K.
The method of claim 6,
The K is a fingerprint fingerprint obtaining device, characterized in that the variable according to the size of the image frame.
The method of claim 5,
The fingerprint input unit,
A fingerprint sensor provided with the fingerprint input window to obtain a fingerprint image;
An image receiver configured to acquire an image input from the fingerprint sensor in units of frames;
And a receiving control unit controlling the image receiving unit to generate the plurality of image frames while the characteristic value of the image acquired through the image receiving unit is out of the range of the reference characteristic value of the image when there is no fingerprint contact. Rotating fingerprint obtaining device characterized in that.

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