CN115393350A - Iris positioning method - Google Patents

Iris positioning method Download PDF

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CN115393350A
CN115393350A CN202211314729.7A CN202211314729A CN115393350A CN 115393350 A CN115393350 A CN 115393350A CN 202211314729 A CN202211314729 A CN 202211314729A CN 115393350 A CN115393350 A CN 115393350A
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iris
pixel
area
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CN115393350B (en
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周辉
倪欢琦
胥虎军
王月虹
伯甘德·肖恩·约瑟夫
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Guangdong Medical Research And Development Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/20—Image enhancement or restoration by the use of local operators
    • G06T5/30—Erosion or dilatation, e.g. thinning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10056—Microscopic image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20036—Morphological image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30041—Eye; Retina; Ophthalmic
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The invention relates to an iris positioning method, which comprises the following steps: s1, performing graphical processing on an original image to obtain a separated iris area outline image; s2, selecting the circle center positioning and range of the iris area outline image according to the obtained separated iris area outline image, and thus completing the iris positioning of the image. The eye interference factors can be accurately eliminated, the recognition deviation is small, and the eye interference eliminating device can be applied to all ophthalmic surgeries operated under a microscope.

Description

Iris positioning method
Technical Field
The invention relates to the technical field of iris recognition, in particular to an iris positioning method.
Background
Iris positioning is an image processing technology for finding the edge of an iris, plays an important role in the field of iris recognition, and is the basis of the accuracy of iris feature extraction. Meanwhile, iris positioning is an essential part in the intelligent process of the ophthalmic surgery.
The traditional iris positioning method mainly comprises the following steps: (1) Circle detection is performed in the iris image, and an iris region is extracted. The method has the advantages that the accuracy is greatly influenced by the image brightness, and the light reflection processing capability is weak. (2) And carrying out edge detection in the iris image, and obtaining a circle radius according to Hough transformation so as to segment the iris area. (3) And extracting the iris edge information by adopting a least square fitting method.
The problems of the method in iris positioning are as follows: the effect is not good when the influence factors such as large-area shielding and eyelash interference exist. In the microscope image during operation, interference items such as bleeding, incomplete eye image, iris non-perfect-circle caused by iris deformation and the like influence the iris detection.
Therefore, there is an urgent need to develop an iris positioning method which can be applied to an ophthalmic surgery scene, can correctly process eye interference factors, is not easy to generate large-amplitude recognition deviation, and can keep consistency for subsequent intelligent surgery operations.
Disclosure of Invention
In view of the above, there is a need for an iris positioning method, which can precisely eliminate the existing eye interference factors, has small recognition deviation, and can be applied to all ophthalmic surgeries under a microscope.
The invention provides an iris positioning method, which comprises the following steps: s1, performing graphical processing on an original image to obtain a separated iris area outline image; and S2, selecting the circle center positioning and range of the iris area outline image according to the obtained separated iris area outline image, thereby completing the iris positioning of the image.
Specifically, the step S1 includes:
s11, converting the original image from a three-channel color image into a single-channel gray image, and uniformly segmenting the single-channel gray image through threshold binarization processing to obtain a binarized image; wherein the original image is a microscope image in an ophthalmic surgery;
s12, performing morphological processing on the obtained binary image to obtain a separated eye multi-contour binary image; wherein, the morphological treatment is to alternately use an opening operation and a closing operation;
s13, carrying out multiple flood filling on the obtained separated eye multi-contour binary image to obtain an eye contour binary image without canthus tissue interference;
step S14, extracting an outermost contour of the obtained binary image of the intraocular contour, calculating the area of the outermost contour, drawing an image of the contour with the largest area, and scanning and filling the image of the largest contour to obtain an initial extraction image of an iris area;
and step S15, repeating the steps S12-S14 for the iris area primary extraction image obtained in the step S14, and obtaining a separated iris area outline image.
Specifically, in step S12: eliminating the protrusion and the tiny connection part of the outline in the binary image by using an opening operation; filling the hole in the outline and repairing the tiny recess on the edge by using a closing operation; the opening and closing operation is alternately used, accidental communication of different areas caused by small gray scale change is eliminated, and meanwhile, the defect of the outline area is filled.
Specifically, in step S13: and performing flood filling on four offset corner points of the separated eye multi-contour binary image to eliminate the contour of an interference object.
Specifically, the flood filling is: for the image with the size of (x y), sequentially taking (a, a), (a, y-a), (x-a, a) and (x-a, y-a) as flooding seed points to carry out flooding filling; wherein, x is the image width, y is the image height, a is the offset, and the unit is pixel.
Specifically, the scan fill includes: map for maximum profileScanning in the row direction and the column direction respectively to completely fill the interior of the outline; the scan in the row direction is: the image with the size of (x y) is scanned line by line and pixel by pixel, and if the pixel with the color of foreground exists in the ith (i belongs to [0, x ]) line, all coordinates are satisfied
Figure 455441DEST_PATH_IMAGE001
Of a pixel
Figure 310264DEST_PATH_IMAGE002
Filling as foreground color, wherein
Figure 762105DEST_PATH_IMAGE002
The coordinates of the pixel to be filled are indicated,
Figure 891735DEST_PATH_IMAGE003
、
Figure 378211DEST_PATH_IMAGE004
respectively representing the pixel coordinates of the first color as the foreground color and the pixel coordinates of the last color as the foreground color in the ith row; for the j (j belongs to [0, y)) line, if there is a pixel with the color of foreground color, all coordinates are satisfied
Figure 935095DEST_PATH_IMAGE005
Is formed by a plurality of pixels
Figure 874232DEST_PATH_IMAGE006
Filled in as foreground color, wherein
Figure 541974DEST_PATH_IMAGE006
The coordinates of the pixel to be filled are represented,
Figure 945273DEST_PATH_IMAGE007
、
Figure 610741DEST_PATH_IMAGE008
respectively representing that the first color of the jth column is the pixel coordinate of the foreground color and the last color is the foreground colorPixel coordinates of the color.
Specifically, the step S2 includes:
s21, carrying out iris area centroid positioning on the separated iris area outline image to obtain a centroid coordinate;
s22, traversing the separated iris area outline images row by row and column by column to obtain the predicted radius r of an iris detection circle;
step S23, using the obtained centroid coordinate as the center of circle, at (r-r) e ， r+ r e ) Performing circle matching within the radius range of the base; wherein r is e An offset is searched for the radius.
Specifically, the step S21 includes:
obtaining centroid coordinates (centrore) x ,centre y ) The specific calculation formula of (2) is as follows:
Figure 99491DEST_PATH_IMAGE009
,
Figure 305344DEST_PATH_IMAGE010
wherein, gray (x, y) is the pixel value at the point (x, y), and n is the total pixel number of the iris area.
Specifically, the step S22 includes:
the calculation method for obtaining the predicted radius r of the iris detection circle is as follows:
Figure 500833DEST_PATH_IMAGE011
wherein x is min And x max X-coordinate values, y-coordinate values of the first iris region pixel and the last iris region pixel in the row direction in the separated iris region profile image respectively min And y max And the y coordinate values of the first iris area pixel and the last iris area pixel in the column direction in the separated iris area outline image are respectively.
Specifically, the step S23 includes:
in the matching process, the pixel gradient is used as an index, and the calculation formula is as follows:
Figure 399519DEST_PATH_IMAGE012
wherein r 'represents the search set of radii of the iris detection circle, r' e (r-r) e ,r+r e ) And R is the final selected iris radius.
The invention is based on microscope images in ophthalmic surgery, through carrying out iris positioning processing on images under the scene in the surgery, the technical problems that the iris detection is influenced by bleeding, incomplete eye images, deformation of the iris and the like in the microscope images are solved, the existing extraocular interference items can be accurately eliminated, the invention is suitable for most of the images with eye deformation, ensures that the identification deviation is small, provides reliable and accurate iris detection of the images in the surgery, realizes accurate iris positioning, accurately segments iris characteristic areas, improves the safety of the surgery, and can be applied to all ophthalmic surgeries operated under the microscope.
Drawings
FIG. 1 is a flow chart of the iris positioning method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Please refer to fig. 1, which is a flowchart illustrating an iris positioning method according to a preferred embodiment of the present invention.
And S1, performing graphical processing on the original image to obtain a separated iris area outline image. The method specifically comprises the following steps:
and S11, converting a three-channel color image into a single-channel gray image for an original image, namely a microscope image in an ophthalmic surgery, and uniformly segmenting the single-channel gray image through threshold binarization processing to obtain a binarized image.
In step S11, the original image is simplified based on the gradation by threshold binarization processing so as to preliminarily extract contour and region feature information of the eye image.
And S12, performing morphological processing on the obtained binary image to obtain a separated eye multi-contour binary image. Wherein the morphological treatment is to alternately use an open operation and a close operation.
In step S12, the protrusion and fine junction of the contour in the binarized image are eliminated using an on operation; a closing operation is used to fill the holes in the profile and repair the edge micro-pits. The opening and closing operation is alternately used, accidental communication of different areas caused by small gray scale change is eliminated, and meanwhile, the defect of the outline area is filled. Through the step, the processed image is converted from the binary image with large-area communication into an image with a plurality of mutually separated outlines.
And S13, performing multiple flood filling on the obtained separated eye multi-contour binary image to obtain an eye contour binary image without the interference of the canthus tissues.
Since periocular tissues and instruments such as eyelids, eyelashes and eyeball holders are frequently found in the microscope image, the above objects are easily recognized as iris regions by mistake in the image, which causes serious hindrance to the recognition effect. In step S13, four offset corner points of the separated eye multi-contour binary image are flood-filled to eliminate the contour of the interfering object and eliminate the negative impact thereof.
Specifically, the method comprises the following steps:
the flood filling is as follows: for the image with the size of (x y), flood filling is carried out by taking (a, a), (a, y-a), (x-a, a) and (x-a, y-a) as the flood seed points in sequence. Wherein x is the image width, y is the image height, a is the offset, and the unit is pixel. In the present embodiment, the offset a =5, and the fill color is the background color black.
And step S14, extracting the outermost contour of the obtained binary image of the intraocular contour, calculating the area of the outermost contour, drawing an image of the contour with the largest area, and scanning and filling the image of the largest contour to obtain an initial iris region extraction image.
In the eye image under the microscope, the area proportion of the iris region of the human eye is the highest in most cases, so after the periocular tissue contour with a large area is removed in step S13, in step S14, the contour with the largest area is the approximate contour of the region where the iris is located.
Wherein the scan padding comprises: for the image of the maximum profile, scanning is performed in the row direction and the column direction respectively, and the interior of the profile is completely filled. The scan in the row direction is: the image with the size of (x y) is scanned line by line and pixel by pixel, and for the ith (i belongs to [0, x ]) line, if the pixel with the color of the foreground exists, in the embodiment, the foreground color is white, all coordinates are satisfied
Figure 375566DEST_PATH_IMAGE001
Of a pixel
Figure 322793DEST_PATH_IMAGE002
Filling in a foreground color white, wherein
Figure 700685DEST_PATH_IMAGE002
The coordinates of the pixel to be filled are represented,
Figure 504693DEST_PATH_IMAGE003
、
Figure 905718DEST_PATH_IMAGE004
respectively representing the pixel coordinate of the first color of the ith row as the foreground color and the pixel coordinate of the last color as the foreground color; for the j (j ∈ [0, y)) th line, if there is a pixel whose color is foreground color white, all coordinates are satisfied
Figure 718953DEST_PATH_IMAGE005
Is formed by a plurality of pixels
Figure 685772DEST_PATH_IMAGE006
Filled to a foreground color white, wherein
Figure 129523DEST_PATH_IMAGE006
The coordinates of the pixel to be filled are represented,
Figure 814582DEST_PATH_IMAGE007
、
Figure 165929DEST_PATH_IMAGE008
respectively representing the pixel coordinate of the j-th column, wherein the first color is the foreground color white and the last color is the foreground color white.
The effect of the scanning filling operation performed in step S14 is to obtain an internally hole-free, edge-flattened, recess-free convex communication region.
And step S15, repeating the steps S12-S14 for the primary extracted iris area image obtained in the step S14 to obtain a separated iris area contour image.
And (5) repeating the steps S12-S14 3-10 times for the initial iris area extraction image obtained in the step S14 to obtain a separated iris area outline image.
In the present embodiment, the steps S12-S14 are repeated 4 times with respect to the iris region initial-extracted image obtained in step S14, and a separated iris region contour image is obtained.
And S2, selecting circle center positioning and range according to the obtained separated iris area outline image, thereby completing iris positioning of the image. The method specifically comprises the following steps:
s21, carrying out iris area centroid positioning on the separated iris area outline image, and acquiring a centroid coordinate (centre) x ,centre y ). The specific calculation formula is as follows:
Figure 190517DEST_PATH_IMAGE009
,
Figure 867486DEST_PATH_IMAGE010
wherein, gray (x, y) is the pixel value at the point (x, y), and n is the total pixel number of the iris area.
In step S21, the centroid is selected as the center of circle reference point, compared to the conventional center selection method (x, y) = ((x, y) =) max +x min ,y max +y min ) /2), the pixel value is taken as the quality index in the step, the center of the area can be judged more accurately, and the deviation caused by uneven distribution of the area is avoided.
Step S22, traversing the separated iris area outline image row by row and column by column to obtain the predicted radius r of the iris detection circle, wherein the calculation method comprises the following steps:
Figure 849564DEST_PATH_IMAGE011
wherein x is min And x max X-coordinate values, y-coordinate values of the first iris region pixel and the last iris region pixel in the row direction in the separated iris region profile image respectively min And y max And the y coordinate values of the first iris area pixel and the last iris area pixel in the column direction in the separated iris area outline image are respectively.
Step S23, using the obtained centroid coordinate as the center of circle, at (r-r) e ， r+ r e ) Is matched with the circle within the radius range of the base. Wherein r is e The offset is searched for the radius.
In the present embodiment, r e =10. In the matching process, the pixel gradient is used as an index, and the calculation formula is as follows:
Figure 473444DEST_PATH_IMAGE012
wherein r 'represents the search set of radii of the iris detection circle, r' e (r-r) e ,r+r e ) And R is the final selected iris radius.
In the step of radius search, a circle is defined for each candidate radius, gray statistics is carried out on all points on the circle, finally, gradient is calculated through convolution, after edge information is obtained, the maximum value of the gradient is selected as the circle closest to the iris outline, and the radius is determined. The method and the device are based on the edge information of the iris area, and the optimal circumference result can be obtained by taking the reliable centroid coordinate as the circle center.
Although the present invention has been described with reference to the presently preferred embodiments, it will be understood by those skilled in the art that the foregoing description is illustrative only and is not intended to limit the scope of the invention, as claimed.

Claims (9)

1. An iris positioning method is characterized by comprising the following steps:
s1, performing graphical processing on an original image to obtain a separated iris area outline image;
s2, selecting circle center positioning and range of the iris area outline image according to the obtained separated iris area outline image so as to complete iris positioning of the image;
wherein, the step S1 comprises:
s11, converting the original image from a three-channel color image into a single-channel gray image, and uniformly segmenting the single-channel gray image through threshold binarization processing to obtain a binarized image; wherein the original image is a microscope image in an ophthalmic surgery;
step S12, performing morphological processing on the obtained binary image to obtain a separated eye multi-contour binary image; wherein, the morphological treatment is to alternately use an opening operation and a closing operation;
s13, carrying out multiple flood filling on the obtained separated eye multi-contour binary image to obtain an eye contour binary image without the interference of eye corner tissues;
step S14, extracting an outermost contour of the obtained binary image of the intraocular contour, calculating the area of the outermost contour, drawing an image of the contour with the largest area, and scanning and filling the image of the largest contour to obtain an initial extraction image of an iris area;
and step S15, repeating the steps S12-S14 for the iris area primary extraction image obtained in the step S14, and obtaining a separated iris area outline image.
2. An iris positioning method according to claim 1, wherein in the step S12: eliminating the protrusion and tiny connection part of the outline in the binary image by using an opening operation; filling the hole in the outline and repairing the tiny recess on the edge by using a closing operation; the opening and closing operation is alternately used, accidental communication of different areas caused by small gray scale change is eliminated, and meanwhile, the defect of the outline area is filled.
3. An iris positioning method as claimed in claim 2, wherein in the step S13: and carrying out flood filling on four offset corner points of the separated eye multi-contour binary image so as to eliminate the contour of an interference object.
4. An iris localization method according to claim 3, wherein the flood filling is: for the image with the size of (x y), sequentially taking (a, a), (a, y-a), (x-a, a) and (x-a, y-a) as flooding seed points to carry out flooding filling; wherein x is the image width, y is the image height, a is the offset, and the unit is pixel.
5. An iris localization method of claim 4 wherein said scan fill-in comprises: for the image with the maximum outline, scanning in the row direction and the column direction respectively, and completely filling the inside of the outline; the scanning in the row direction is: the image with the size of (x y) is scanned line by line and pixel by pixel, and for the ith (i belongs to [0, x)) line, if the pixel with the color of the foreground color exists, all the coordinates are satisfied
Figure DEST_PATH_IMAGE001
Is formed by a plurality of pixels
Figure 565740DEST_PATH_IMAGE002
Filled in as foreground color, wherein
Figure 164212DEST_PATH_IMAGE002
The coordinates of the pixel to be filled are represented,
Figure DEST_PATH_IMAGE003
、
Figure 40901DEST_PATH_IMAGE004
respectively representing the pixel coordinates of the first color as the foreground color and the pixel coordinates of the last color as the foreground color in the ith row; for the j (j ∈ [0, y)) th line, if there is a pixel whose color is the foreground color, all coordinates are satisfied
Figure DEST_PATH_IMAGE005
Is formed by a plurality of pixels
Figure 427145DEST_PATH_IMAGE006
Filling as foreground color, wherein
Figure 287654DEST_PATH_IMAGE006
The coordinates of the pixel to be filled are indicated,
Figure DEST_PATH_IMAGE007
、
Figure 220974DEST_PATH_IMAGE008
and respectively representing the pixel coordinate of the first color of the jth column as the foreground color and the pixel coordinate of the last color as the foreground color.
6. An iris positioning method as claimed in claim 1, wherein the step S2 includes:
s21, carrying out iris area centroid positioning on the separated iris area outline image to obtain a centroid coordinate;
s22, traversing the separated iris area outline images row by row and column by column to obtain the predicted radius r of an iris detection circle;
step S23, using the obtained barycentric coordinates as a circleHeart in (r-r) e ， r+ r e ) Performing circle matching within the radius range of the base; wherein r is e The offset is searched for the radius.
7. An iris positioning method according to claim 6, wherein said step S21 comprises:
obtaining centroid coordinates (centrore) x ,centre y ) The specific calculation formula of (2) is as follows:
Figure DEST_PATH_IMAGE009
,
Figure 952170DEST_PATH_IMAGE010
wherein, gray (x, y) is the pixel value at the point (x, y), and n is the total number of pixels in the iris area.
8. An iris positioning method as claimed in claim 7, wherein the step S22 includes:
the calculation method for obtaining the predicted radius r of the iris detection circle is as follows:
Figure 539009DEST_PATH_IMAGE012
wherein x is min And x max X coordinate value, y coordinate value of the first iris region pixel and the last iris region pixel in the row direction in the separated iris region outline image min And y max And the y coordinate values of the first iris area pixel and the last iris area pixel in the column direction in the separated iris area outline image are respectively.
9. An iris positioning method as claimed in claim 8, wherein the step S23 includes:
in the matching process, the pixel gradient is used as an index, and the calculation formula is as follows:
Figure DEST_PATH_IMAGE013
wherein r 'represents the search set of radii of the iris detection circle, r' e (r-r) e ,r+r e ) And R is the final selected iris radius.
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