WO2024037267A1 - 一种眼球活动度的评估方法、***和存储介质 - Google Patents

一种眼球活动度的评估方法、***和存储介质 Download PDF

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Publication number
WO2024037267A1
WO2024037267A1 PCT/CN2023/107803 CN2023107803W WO2024037267A1 WO 2024037267 A1 WO2024037267 A1 WO 2024037267A1 CN 2023107803 W CN2023107803 W CN 2023107803W WO 2024037267 A1 WO2024037267 A1 WO 2024037267A1
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eye
eyeball
bitmap
angle
movement
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PCT/CN2023/107803
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English (en)
French (fr)
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田超楠
王友翔
王友志
杜东
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上海佰翊医疗科技有限公司
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Publication of WO2024037267A1 publication Critical patent/WO2024037267A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/113—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining or recording eye movement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/14—Arrangements specially adapted for eye photography
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Definitions

  • This application belongs to the field of eye detection technology, and specifically relates to an eyeball activity assessment method, device and storage medium.
  • the oculomotor, trochlear, and abducens nerves have the function of controlling the movement of the extraocular muscles of the eye and are called oculomotor nerves.
  • oculomotor nerves When the above nerves or nerve nuclei are damaged individually or combined, eye movement or diplopia may occur. When complete damage occurs, all extraocular muscles will be paralyzed and the eyeballs will become immobile. Extraocular muscle paralysis caused by extraocular muscle injury, infection or myopathy may also cause eye movement failure, which is clinically referred to as eye movement disorder. Eye movement disorders may also be related to medical diseases, including orbital diseases, diabetes, neuroinflammation, etc. Therefore, how to evaluate the eye movement ability of one eye and both eyes is of great significance for eye detection.
  • the detection of eye movement is usually done manually by a doctor.
  • the specific detection methods are as follows: 1) Eye movement examination of one eye: cover the opposite eye, starting from the first eye position, instruct the patient to look at the flashlight, along the Movement in the diagnostic direction; 2) Eye movement examination of both eyes: Starting from the first eye position, ask the patient to gaze at the flashlight and move in the diagnostic direction of gaze. Binocular movement examination can evaluate the relative position of the eyes in eye movement and obtain different information from monocular examination.
  • the above-mentioned detection methods do not have objective data, and cannot record every change of the patient, and cannot form continuous data.
  • the prior art also discloses the use of automatic detection methods to detect eye movement.
  • the patient's head is fixed through a head fixation frame.
  • An indicator light is arranged in front of the head holder.
  • the indicator light emits a visible light beam in a direction away from the subject's eyes.
  • the visible light beam extends beyond the subject's static field of view.
  • the imaging lens is arranged in front of the head holder. The imaging lens is used to capture images of the subject's eyeballs as they rotate along the direction of the visible light beam. The subject's eyeball movements are obtained through the eye images captured by the imaging lens.
  • the eye images are not specified.
  • the differentiation and processing of eye movement conditions lead to insufficient detection accuracy of eye movements; for example, the Chinese patent "A computer-based eye movement distance and binocular movement consistency deviation detection device and method" (Application No.: 201710054692.1, publication date: June 2017 13), the limbus extraction unit extracts the limbus in the reference photo sent by the camera and each test photo, and calculates the movement distance of the eyeball in each direction through the points extracted on the limbus, so as to achieve consistent movement of both eyes.
  • the limbus is the transition zone between the cornea and the sclera, the extracted limbus boundary is not clear enough, which will also affect the accuracy of the final result.
  • the purpose of this application is to provide a method and system for evaluating eye movement, aiming to improve the accuracy of eye movement assessment and eliminate errors in the measurement process.
  • the activity angle of the eyeball activity is calculated, thereby achieving an accurate assessment of the eyeball activity.
  • this application provides a method for evaluating eye movement, which includes the following steps:
  • Step S1 In the near-infrared light field of 700-1200nm, capture the first eye bitmap of the user looking straight ahead at the position in front of the eyeball;
  • Step S2 Shoot in front of the eyeball to obtain the second eye bitmap and the third eye bitmap when the user's eyeball moves to the extreme position in the direction to be measured;
  • Step S3 Compare the first eye bitmap with the second eye bitmap and the third eye bitmap respectively, and calculate the movement angle of the eyeball movement.
  • the direction to be measured includes eyeball upward, downward, inward, outward, inward upward, outward upward, inward downward, and outward downward.
  • step S3 includes: using a convolutional neural network to segment the pupil from the images of the first eye bitmap, the second eye bitmap, and the third eye bitmap;
  • the central angle ⁇ corresponding to the straight line A and the central angle ⁇ corresponding to the straight line B are obtained, and the central angle ⁇ and the central angle ⁇ are added to obtain the active angle.
  • the movable angle is compensated by the amplitude of pupil change, the amplitude of eyeball center displacement, and corneal refraction error compensation in the first eye position map, the second eye position map, or the third eye position map.
  • the specific method of compensating the activity angle through the amplitude of pupil changes in the first eye bitmap, the second eye bitmap or the third eye bitmap is: by obtaining the first eye bitmap, the second eye bitmap or The amplitude of the pupil change in the third eye bitmap compensates for the position of the edge point P2.
  • the activity angle is compensated by the amplitude of the eyeball center displacement in the first eye bitmap, the second eye bitmap or the third eye bitmap, specifically: obtaining the first eye bitmap, the second eye bitmap or The overlapping image formed by the different degrees of displacement of the eyeball center in the third eye position map is reversely translated to offset the impact of the displacement on the movable angle.
  • the compensation of the movable angle through corneal refraction error compensation in the first eye position map, the second eye position map or the third eye position map is specifically: the angle compensated by the corneal refraction error compensation and the movable angle into a linear relationship.
  • this application provides an eye movement assessment device, including:
  • the first acquisition module is used to capture the first eye bitmap of the user looking straight ahead in the near-infrared light field of 700-1200nm at the position in front of the eyeball;
  • the second acquisition module is used to capture the second eye bitmap and the third eye bitmap when the user's eyeball moves to the extreme position in the direction to be measured by shooting in front of the eyeball;
  • the image processing module is used to compare the first eye bitmap with the second eye bitmap and the third eye bitmap respectively, and calculate the movement angle of the eyeball movement.
  • the present application provides a computer-readable storage medium in which at least one program code is stored, and the at least one program code is loaded and executed by a processor to implement the eye movement assessment method. The operation performed.
  • the amplitude of pupil changes before and after eye movement, the amplitude of eyeball center displacement, and corneal refraction error compensation are used to compensate the movable angle, which can further improve the calculation accuracy of the movable angle, thereby accurately calculating the eyeball
  • the activity angle in each direction to be measured provides a more accurate basis for eye detection.
  • Figure 1 is a flow chart of the eye movement assessment method in this application.
  • Figure 2 shows eye images captured under visible light and near-infrared light
  • Figure 3 is an overlapping image of the second eye bitmap or the third eye bitmap and the first eye bitmap taken in each direction to be measured;
  • Figure 4 is a calculation diagram of the eye movement angle
  • Figure 5 shows the pupil changes before and after eye movement
  • Figure 6 is an overlay image of eyeball imaging before and after eye movement
  • Figure 7 shows the displacement of the eyeball center before and after eye movement
  • Figure 8 is a refraction diagram of the corneal lens imaging the pupil
  • Figure 9 shows the activity angle calculated using the pupil edge and iris edge
  • Figure 10 is a schematic structural diagram of an eyeball activity evaluation device.
  • this embodiment 1 provides a method for evaluating eye movement.
  • the evaluation method includes the following steps:
  • Step S1 In the near-infrared light field of 700-1200nm, the user looks straight ahead and obtains the first eye bitmap taken in front of the user's eyes;
  • Step S2 Obtain the second eye bitmap and the third eye bitmap in which the eyeball photographed in front of the user's eye moves to the extreme position in the direction to be measured;
  • Step S3 Compare the first eye bitmap with the second eye bitmap and the third eye bitmap respectively, and calculate the movement angle of the eyeball movement.
  • the user's head is first fixed, for example, the user's head is fixed through forehead rests, chin rests, and eye corner fixing points. After fixing, take a first-eye bitmap of the user's eyes looking straight ahead in an infrared red light field of 700-1200, and a second-eye image of the user turning their eyeballs to the extreme position in accordance with the directions indicated by the indicator lights in each direction to be measured. Bitmap, third eye bitmap.
  • eye position refers to the position of the eyeball during an eye examination, which is divided into first eye position, second eye position, and third eye position.
  • the first eye position refers to the eye position with both eyes looking straight ahead at infinity on the horizontal plane.
  • the second eye position refers to the eye position when the eyeballs rotate upward, downward, inward and outward.
  • the third eye position refers to the eyeballs turning inward and upward. , the position of the eyes when turning obliquely from inside to bottom, outside to top, and outside to bottom, that is, the eye position when turning to the upper nose, lower nose, upper temporal, and lower temporal.
  • the first, second, and third eye bitmaps respectively refer to images taken when the eyeball is in each eye position.
  • the directions to be measured include eyeball upward, downward, inward, outward, inward upward, outward upward, inward downward, and outward downward.
  • Each eye is measured in eight directions to be measured. Active angle, each time one eye is measured, the other eye is covered.
  • Indicators set in each direction to be measured are used to instruct the left eye and right eye to repeat the rotation in each direction above, and multiple second eye bitmaps are obtained.
  • the third eye bitmap is compared with the first eye bitmap as a reference to calculate the movement angle of the eyeball movement.
  • the above-mentioned activity angle refers to the maximum angle at which the eyeball body rotates around the center of the eyeball before and after eyeball movement.
  • this Embodiment 2 further limits the calculation method of the activity angle. Specifically:
  • the central angle ⁇ corresponding to the straight line A and the central angle ⁇ corresponding to the straight line B are obtained, and the central angle ⁇ and the central angle ⁇ are added to obtain the activity angle ⁇ .
  • each direction to be measured such as the inner-upper, inner-lower, outer-upper, and outer-lower directions of oblique eyeball movement, can be used to obtain the first, second, and third eyes.
  • the above calculation of the active angle is achieved through image and data processing steps.
  • this Embodiment 3 further limits the compensation method of the movable angle, thereby improving the calculation accuracy of the movable angle.
  • the changes in the pupil before and after eye movement, the displacement of the eyeball center, and the influence of corneal refraction will all bring errors to the calculation of the active angle.
  • the compensation methods for the above errors will be explained in detail below.
  • the pupil image when the eyeball rotates away from emmetropia, the pupil image will become an ellipse, and the direction of flattening is in the direction of rotation, while the image perpendicular to the direction of rotation is not affected. So if there is a change in the pupil diameter in the direction perpendicular to the rotation, it comes from the change in the pupil. If the diameter of emmetropia is smaller than that of strabismus, the pupil will dilate when it rotates; if the diameter of emmetropia is larger than that of strabismus, the pupil will shrink when it rotates. For example, if the ellipse perpendicular to the direction of rotation shrinks, it comes from the contraction of the pupil.
  • the positions of the two divided circles with a straight line take the diameters of the two ellipses perpendicular to the straight line, and use the above two diameters to calculate the pupil contraction.
  • the position of the edge point P2 can be compensated by the amplitude of the pupil change, thereby eliminating the impact of pupil contraction on the accuracy of the calculation of the active angle, thereby passing the first
  • the amplitude of the pupil change in the eye position map, the second eye position map or the third eye position map compensates for the activity angle.
  • the left picture of Figure 7 shows the change of the eyeball before and after the inward and outward rotation, taken from the direction of the top of the human skull
  • the right picture of Figure 7 shows the upward and downward movement of the eyeball taken from the direction of the top of the human skull. Changes in direction before and after rotation. Since the displacement of the eyeball center before and after the eyeball rotates has no impact on the image taken by the camera directly in front, it can be ignored. Only the image of the eyeball projected onto the cross-section is taken. Statistics show the direction of eyeball movement and the position of the eyeball in the cross-section. The relationship between the center displacement is as follows:
  • the eyeball center displacement and eyeball rotation angle are linear rules. If the eyeball rotation angle is 0° (emmetropia), the eyeball center displacement is 0mm. The relationship between the above displacement and angle can be calculated in advance to correct the eyeball movement angle calculation. The position of the center C2 is thereby compensated for the activity angle by the amplitude of the eyeball center displacement in the first eye bitmap, the second eye bitmap or the third eye bitmap.
  • the edge point of the pupil is affected by the refraction of the corneal crystal.
  • the edge point of the pupil in the picture is not the real position, and the edge point of the iris is not affected by it because it does not penetrate the cornea. Influence.
  • pupil edge point and iris edge point for the same photo, different activity angles can be obtained.
  • the calculation using pupil edge point has corneal refraction error. Through experimental measurements, it can be found that the difference in the activity angle calculated through the pupil and iris is highly linear.
  • the formula for calculating the activity angle to compensate for the corneal refractive error is as follows:
  • the activity angle ⁇ is the calculated activity angle before corneal refractive error compensation.
  • the error in the calculation of the movable angle can be eliminated, and an accurate movable angle can finally be obtained.
  • this application provides an eyeball activity evaluation device, as shown in Figure 10, including: a first acquisition module 1001, a second acquisition module 1002, and an image processing module (1003), where
  • the first acquisition module 1001 is used to capture the first eye bitmap of the user looking straight ahead at the position in front of the eyeball in the near-infrared light field of 700-1200nm;
  • the second acquisition module 1002 is used to capture the second eye bitmap and the third eye bitmap when the user's eyeball moves to the extreme position in the direction to be measured at a position in front of the eyeball;
  • the image processing module 1003 is used to compare the first eye bitmap with the second eye bitmap and the third eye bitmap respectively, and calculate the movement angle of the eyeball movement.
  • the present application provides a computer-readable storage medium in which at least one program code is stored, and the at least one program code is loaded and executed by a processor to implement the eye movement assessment method. The operation performed.
  • a computer-readable storage medium including a memory storing at least one program code.
  • the at least one program code is loaded and executed by the processor to complete the eye movement degree in the above embodiment. evaluation method.
  • the computer-readable storage medium can be read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), read-only compact disc (Compact Disc Read-Only Memory, CDROM), magnetic tape, Floppy disks and optical data storage devices, etc.

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Abstract

本发明涉及一种眼球活动度的评估方法、***和存储介质。所述评估方法包括：在700-1200nm的近红外光光场中，在眼睛前方位置拍摄获取用户平视前方的第一眼位图；在眼睛前方位置拍摄获取用户眼球沿待测方向运动到极限位置的第二眼位图和第三眼位图；将第一眼位图分别与第二眼位图和第三眼位图进行对比，计算眼球活动度的活动角。本发明提供的技术方案在近红外光光场中拍摄眼部图像，有效地区分虹膜、瞳孔，从而准确地识别瞳孔边缘，再采用不同眼位图的对比计算眼球活动角，并通过补偿进一步提高活动角的计算精度，从而准确地计算出眼球在各个待测方向上的活动角。

Description

一种眼球活动度的评估方法、***和存储介质 技术领域
本申请属于眼部检测技术领域，具体涉及一种眼球活动度的评估方法、装置和存储介质。
背景技术
动眼、滑车、外展神经具有支配眼球眼外肌运动的功能，称为眼球运动神经。当上述神经或神经核单独或合并受损时，可出现眼球运动不能或复视，完全损害时出现眼外肌全部瘫痪，眼球固定不动。眼外肌损伤、感染或肌病导致的眼外肌麻痹，也可出现眼球运动不能，临床统称为眼球运动障碍。眼球运动障碍还可能与内科疾病相关，包括眼眶疾病、糖尿病、神经炎症等，因此如何评估单眼及双眼的眼球转动能力，对于眼部检测具有重要的意义。
现有技术中，眼球活动度的检测通常采用医生手动测量的方式，具体检测方法如下：1)单眼的眼球运动检查：遮盖对侧眼，自第一眼位开始，嘱患者注视手电筒，沿注视的诊断方向运动；2)双眼的眼球运动检查：自第一眼位开始，嘱患者注视手电筒，沿注视的诊断方向运动。双眼运动检查，可以评估眼球运动的双眼相对位置，获取单眼检查不同的信息。但是，上述检测方法，没有客观的数据，且无法记录患者每次的变化，无法形成连续数据。
此外，现有技术中还公开了采用自动检测方式来检测眼球活动度。如中国发明专利“一种眼球活动度检测仪”(申请号：202011260253.4，公开日：2021年2月19日)所述，通过头部固定架固定患者的头部， 指示灯设置在头部固定架前方，所述指示灯朝向远离受试者眼部的方向上发出可见光束，可见光束延伸到受试者静视野之外，成像镜头设置在头部固定架前方，成像镜头用于拍摄受试者眼球沿着可见光束的方向转动时的图像，通过成像镜头拍摄的眼部图像获得受试者的眼球活动情况，但是，上述方案中，未对眼部图像做具体的区分和处理，导致眼球活动情况的检测精度不够；如中国专利“一种基于计算机的眼球运动距离及双眼运动一致性偏差检测装置及方法”(申请号：201710054692.1，公开日：2017年6月13日)所述，通过角膜缘提取单元提取照相机发来的基准照片和各个测试照片中的角膜缘，通过角膜缘上提取的点来计算眼球在各个方向上的运动距离，从而进行双眼运动一致性偏差计算，但是，由于角膜缘为角膜和巩膜之间的过渡带，提取到的角膜缘的边界不够清晰，也会影响到最终结果的精度。
发明内容
本申请的目的是提供一种眼球活动度的评估方法和***，旨在提高眼球活动度评估的精度，消除测量过程中的误差。通过采集用户在近红外光光场的多个不同眼位图，再对采集的多个不同眼位图像进行分析，计算眼球活动度的活动角，进而实现对眼球活动度的准确评估。
为了实现上述目的，一方面，本申请提供一种眼球活动度的评估方法，所述评估方法包括以下步骤：
步骤S1：在700-1200nm的近红外光光场中，在眼球前方位置拍摄获取用户平视前方的第一眼位图；
步骤S2：在眼球前方位置拍摄获取用户眼球沿待测方向运动到极限位置的第二眼位图和第三眼位图；
步骤S3：将所述第一眼位图分别与所述第二眼位图和第三眼位图进行对比，计算眼球活动度的活动角。
进一步地，所述待测方向包括眼球向上、向下、向内、向外、向内上、向外上、向内下、向外下。
进一步地，所述步骤S3包括：采用卷积神经网络，从所述第一眼位图、第二眼位图、第三眼位图的图像中分割瞳孔；
取出第一眼位图的圆心C1、第二眼位图或第三眼位图的圆心C2，并用直线连接圆心C1和圆心C2；
沿所述直线找到所述第一眼位图与所述第二眼位图或第三眼位图的瞳孔的同一点运动前后的边缘点P1、P2；
将所述边缘点P1和P2连接成直线P1P2；
通过垂直于所述直线P1P2并经过所述圆心C1的直线将所述直线P1P2分割成两段，即直线A和直线B；
通过眼球半径r，获取直线A对应的圆心角α以及直线B对应的圆心角β，将所述圆心角α和所述圆心角β相加得到所述活动角。
进一步地，通过第一眼位图、第二眼位图或第三眼位图中瞳孔变化的幅度、眼球中心位移的幅度、角膜折射误差补偿对所述活动角进行补偿。
进一步地，通过第一眼位图、第二眼位图或第三眼位图中瞳孔变化的幅度对所述活动角进行补偿具体为：通过获取第一眼位图、第二眼位图或第三眼位图中瞳孔变化的幅度补偿所述边缘点P2的位置。
具体地，计算第一眼位图、第二眼位图或第三眼位图中瞳孔直径沿着与待测方向垂直的方向变化的幅度，利用所述幅度等比例地补偿所述边缘点P2的位置。
进一步地，通过第一眼位图、第二眼位图或第三眼位图中眼球中心位移的幅度对所述活动角进行补偿具体为：获取第一眼位图、第二眼位图或第三眼位图中眼球中心不同程度位移形成的重叠成像，将所述重叠成像进行逆向平移以抵消所述位移对活动角的影响。
进一步地，通过第一眼位图、第二眼位图或第三眼位图中角膜折射误差补偿对所述活动角进行补偿具体为：通过角膜折射误差补偿所补偿的角度与所述活动角成线性关系。
一方面，本申请提供了一种眼球活动度的评估装置，包括：
第一获取模块，用于在700-1200nm的近红外光光场中，在眼球前方位置拍摄获取用户平视前方的第一眼位图；
第二获取模块，用于在眼球前方位置拍摄获取用户眼球沿待测方向运动到极限位置的第二眼位图和第三眼位图；
图像处理模块，用于将该第一眼位图分别与第二眼位图和第三眼位图进行对比，计算眼球活动度的活动角。
一方面，本申请提供了一种计算机可读存储介质，该计算机可读存储介质中存储有至少一条程序代码，所述至少一条程序代码由处理器加载并执行以实现该眼球活动度的评估方法所执行的操作。
本申请的技术方案相较于现有技术，至少具有如下有益效果：
在近红外光光场中拍摄眼部图像，可以有效地区分虹膜、瞳孔，从而准确地识别瞳孔边缘，通过采用瞳孔边缘点的位移计算眼球活动角，避免了现有技术中采用虹膜边缘计算眼球活动角带来的误差大的缺点。
进一步地，本申请中采用眼球运动前后瞳孔变化的幅度、眼球中心位移的幅度、角膜折射误差补偿对所述活动角进行补偿，可以近一步提高对于活动角的计算精度，从而准确地计算出眼球在各个待测方向上的活动角，从而为眼部检测提供更为准确的判定依据。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例或现有技术描述中所需要使用的附图作简单的介绍。
图1为本申请中的眼球活动度的评估方法的流程图；
图2为可见光与近红外光下拍摄到的眼部图像；
图3为在各个待测方向上拍摄的第二眼位图或第三眼位图与第一眼位图的重叠图像；
图4为眼球活动角的计算图；
图5为眼球运动前后的瞳孔变化图；
图6为眼球运动前后眼球成像的重叠图像；
图7为眼球运动前后眼球中心的位移图；
图8是角膜晶体对瞳孔成像的折射图；
图9为采用瞳孔边缘和虹膜边缘计算的活动角；
图10为眼球活动度的评估装置的结构示意图。
具体实施方式
下面结合附图和实施例，对本申请的具体实施方式作进一步详细描述。以下实施例用于说明本申请，但不用来限制本申请的范围。
一方面，如图1所示，本实施例1提供了一种眼球活动度的评估方法，该评估方法包括以下步骤：
步骤S1：在700-1200nm的近红外光光场中，用户平视前方，获取在用户的眼睛前方拍摄的第一眼位图；
步骤S2：获取在所述用户的眼睛前方拍摄的眼球沿待测方向运动到极限位置的第二眼位图、第三眼位图；
步骤S3：将所述第一眼位图分别与所述第二眼位图、第三眼位图进行对比，计算眼球活动度的活动角。
在具体步骤中，采用获取装置获取眼部图像时，先固定用户的头部，如通过额托、颌托、眼角固定点实现用户的头部固定。固定好之后，在700-1200的红外红光光场中拍摄用户眼睛正视前方的第一眼位图，以及用户随着各个待测方向的指示灯指示方向将眼球转动到极限位置的第二眼位图、第三眼位图。
需要说明的是，眼位是指在眼科检查中眼球的位置，分为第一眼位、第二眼位、第三眼位。第一眼位是指两眼在水平面上平视前方无限远处的眼位，第二眼位是指眼球向上、下、内、外转动时的眼位，第三眼位是指眼球向内上、内下、外上、外下作斜向转动时的眼位，即向鼻上、鼻下、颞上、颞下转动时的眼位。相应地，第一、第二、第三眼位图分别指眼球在各个眼位时拍摄的图像。
如图2所示，在正常可见光的波段400-700nm中，眼睛不同部分，即瞳孔、虹膜、巩膜的颜色对成像几乎不起作用，由于虹膜与巩膜接触部分的角膜缘的渐变式结构，导致无法准确地识别眼球的球心。人类黑色素色素的吸收峰值发生在335nm左右，而对于波长超过700nm的波段几乎完全不吸收，而虹膜的反射率在波长超过700nm的近红外线波段内是相当稳定的，因此，采用近红外光光场，可以很好地区分巩膜、虹膜、瞳孔边界，从而可以更好地提升算法的准确性与稳定性。
如图3所示，待测方向包括眼球向上、向下、向内、向外、向内上、向外上、向内下、向外下，每只眼睛分别在八个待测方向上测量活动角，每次测量一只眼睛时遮挡另一只眼睛，采用各个待测方向上设置的指示灯分别指示左眼、右眼重复上述各个方向的转动，并获取多张第二眼位图、第三眼位图，以分别与作为基准的第一眼位图进行对比，从而计算出眼球活动度的活动角。
需要说明的是，上述活动角是指眼球活动前后眼球体绕眼球球心转动的最大角度。
实施例2
如图4所示，基于上述方法的实施例1，本实施例2进一步限定了活动角的计算方式。具体为：
采用卷积神经网络，从所述第一眼位图、眼球向下运动到极限位置的第二眼位图的图像中分割瞳孔；
取出第一眼位图的圆心C1和第二眼位图的圆心C2；用直线连接圆心C1和圆心C2；
沿所述直线找到所述第一眼位图与所述第二眼位图的瞳孔的同一点运动前后的边缘点P1、P2；
将所述边缘点P1和P2连接成直线P1P2；
通过垂直于所述直线P1P2并经过所述圆心C1的直线将所述直线P1P2分割成两段，即直线A和直线B；
通过眼球半径r，获取直线A对应的圆心角α以及直线B对应的圆心角β，将所述圆心角α和所述圆心角β相加得到所述活动角θ。
上述计算方式中，通过简单的解析几何关系，通过计算球面上弧长所对应的圆心角，即可求出眼球运动前后的活动角。需要说明的是，由于眼球为规则的球面结构，各个待测方向，例如眼球斜向运动的内上、内下、外上、外下方向，均可在获取第一、第二、第三眼位图后，通过图像和数据处理步骤实现上述活动角的计算。
实施例3
如图5-7所示，基于上述方法的实施例2，本实施例3进一步限定了活动角的补偿方式，从而能够提高活动角的计算精度。在实际测量中发现，眼球运动前后瞳孔的变化、眼球中心的位移、角膜折射的影响，均会对活动角的计算带来误差，下面将具体解释对上述几种误差的补偿方式。
首先，如图5所示，当眼球转动偏离了正视时，瞳孔成像会变成一个椭圆，变扁方向在转动的方向上，而垂直于转动的方向成像不受影响。所以如果垂直于转动的方向上的瞳孔直径有变化，则来自于瞳孔的变化。如果正视比斜视的直径小，则瞳孔转动时有放大，如果正视比斜视的直径大，则瞳孔转动时有缩小。例如，如果垂直于转动方向上的椭圆有缩小，就来自于瞳孔的收缩，将分割出来的两个圆心连出直线，取出两个椭圆上垂直于直线的直径，拿上述两个直径计算瞳孔收缩的比例，等比例地矫正直线上用来计算的椭圆边缘点，即可通过瞳孔变化的幅度补偿所述边缘点P2的位置，借此消除瞳孔收缩对活动角计算精度的影响，从而通过第一眼位图、第二眼位图或第三眼位图中瞳孔变化的幅度对所述活动角进行补偿。
如图6所示，当眼睛在转动时，眼睛并非在空间中悬浮不动，由于周遭都是软组织还有眼肌的发力不均，不同方向的眼球转动会引起不同程度的眼球中心的位移。眼球转动角度越大，眼球中心的位移就越多。眼球中心的位移对算法的影响相当于在重叠对齐正视和侧视的成像时发生了错位，导致计算出来的活动角过大或过小。补偿的方法是知道眼球中心位移多少后，重叠成像时有意反方向错位，抵消掉位移的影响。
如图7所示，图7的左图表示从人体颅顶方向所拍摄的眼球向内、外方向转动前后的变化图，图7的右图表示从人体颅顶方向所拍摄的眼球向上、下方向转动前后的变化图。由于眼球转动前后，前后方向的眼球中心的位移对正前方相机拍出的成像没有影响，因此可以忽略不计，只取眼球投影到横截面上的图像，统计显示眼球运动的方向和眼球在横截面上的中心位移的关系如下：
眼球向内旋转30°的位移：眼球中心向内0.69mm；
眼球向外旋转30°的位移：眼球中心向外0.45mm；
眼球向上旋转20°的位移：眼球中心向下0.43mm；
眼球向下旋转20°的位移：眼球中心向上0.43mm；
并且，眼球中心位移和眼球转动角度为线性规律，如果眼球转动角度为0°时(正视)则眼球中心位移为0mm，可以通过预先统计的上述位移和角度的关系来修正活动角计算中眼球球心C2的位置，从而通过第一眼位图、第二眼位图或第三眼位图中眼球中心位移的幅度对所述活动角进行补偿。
如图8所示，在计算活动角时，瞳孔的边缘点受到角膜晶体的折射影响，画面中瞳孔边缘点并不是现实真实的位置，而虹膜边缘点则因不穿透角膜而不会受其影响。同照片采用瞳孔边缘点与虹膜边缘点两种算法，可得出不同的活动角，其中采用瞳孔边缘点进行计算是带有角膜折射误差的。通过实验测量可得，通过瞳孔和虹膜计算出的活动角的差别成高度线性，遂得对角膜折射误差进行补偿的活动角计算公式如下：
活动角θ的补偿＝0.13134×活动角θ+0.52704
修正后的活动角θ＝活动角θ+活动角θ的补偿
上述公式中，活动角θ为未经角膜折射误差补偿前的计算活动角。
将上述眼球运动前后瞳孔的变化、眼球中心的位移、角膜折射的影响对活动角的影响均考虑在内并进行相应的补偿后，即可消除活动角计算中的误差，最终得到精确的活动角。
一方面，本申请提供了一种眼球活动度的评估装置，如图10所示，包括：第一获取模块1001、第二获取模块1002和图像处理模块(1003)，其中
第一获取模块1001，用于在700-1200nm的近红外光光场中，在眼球前方位置拍摄获取用户平视前方的第一眼位图；
第二获取模块1002，用于在眼球前方位置拍摄获取用户眼球沿待测方向运动到极限位置的第二眼位图和第三眼位图；
图像处理模块1003，用于将该第一眼位图分别与第二眼位图和第三眼位图进行对比，计算眼球活动度的活动角。
一方面，本申请提供了一种计算机可读存储介质，该计算机可读存储介质中存储有至少一条程序代码，所述至少一条程序代码由处理器加载并执行以实现该眼球活动度的评估方法所执行的操作。
关于上述实施例中的眼球活动度的评估装置，其中各个模块执行操作的具体方式已经在方法实施例中进行了详细描述，相关之处参见方法实施例的部分说明。
在示例性实施例中，还提供了一种计算机可读存储介质，包括存储有至少一条程序代码的存储器，所述至少一条程序代码由处理器加载并执行以完成上述实施例中的眼球活动度的评估方法。例如，该计算机可读存储介质可以是只读存储器(Read-Only Memory,ROM)、随机存取存储器(Random Access Memory，RAM)、只读光盘(Compact Disc Read-Only Memory，CDROM)、磁带、软盘和光数据存储设备等。
本领域普通技术人员可以理解实现上述实施例的全部或部分步骤可以通过硬件来完成，也可以通过程序来至少一条程序代码相关的硬件完成，该程序可以存储于一种计算机可读存储介质中，上述提到的存储介质可以是只读存储器，磁盘或光盘等。
以上所述仅为本申请的较佳实施例而已，并不用以限制本申请，凡在本申请的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本申请的保护范围之内。

Claims (10)

  1. 一种眼球活动度的评估方法，其特征在于，所述评估方法包括：
    步骤S1：在700-1200nm的近红外光光场中，在眼球前方位置拍摄获取用户平视前方的第一眼位图；
    步骤S2：在眼球前方位置拍摄获取用户眼球沿待测方向运动到极限位置的第二眼位图和第三眼位图；
    步骤S3：将所述第一眼位图分别与所述第二眼位图和第三眼位图进行对比，计算眼球活动度的活动角。
  2. 根据权利要求1所述的眼球活动度的评估方法，其特征在于，所述待测方向包括眼球向上、向下、向内、向外、向内上、向外上、向内下、向外下。
  3. 根据权利要求1或2所述的眼球活动度的评估方法，其特征在于，所述步骤S3包括：
    采用卷积神经网络，从所述第一眼位图、第二眼位图、第三眼位图的图像中分割瞳孔；
    取出第一眼位图的圆心C1、第二眼位图或第三眼位图的圆心C2，并用直线连接圆心C1和圆心C2；
    沿所述直线找到所述第一眼位图与所述第二眼位图或第三眼位图的瞳孔的同一点运动前后的边缘点P1、P2；
    将所述边缘点P1和P2连接成直线P1P2；
    通过垂直于所述直线P1P2并经过所述圆心C1的直线将所述直线P1P2分割成两段，即直线A和直线B；
    通过眼球半径r，获取直线A对应的圆心角α以及直线B对应的圆心角β，将所述圆心角α和所述圆心角β相加得到所述活动角。
  4. 根据权利要求3所述的眼球活动度的评估方法，其特征在于，通过第一眼位图、第二眼位图或第三眼位图中瞳孔变化的幅度、眼球中心位移的幅度、角膜折射误差补偿对所述活动角进行补偿。
  5. 根据权利要求4所述的眼球活动度的评估方法，其特征在于，通过第一眼位图、第二眼位图或第三眼位图中瞳孔变化的幅度对所述活动角进行补偿具体为：通过获取所述第一眼位图、所述第二眼位图或第三眼位图中瞳孔变化的幅度补偿所述边缘点P2的位置。
  6. 根据权利要求5所述的眼球活动度的评估方法，其特征在于，计算第一眼位图、第二眼位图或第三眼位图中瞳孔直径沿着与待测方向垂直的方向变化的幅度，利用所述幅度等比例地补偿所述边缘点P2的位置。
  7. 根据权利要求4所述的眼球活动度的评估方法，其特征在于，通过第一眼位图、第二眼位图或第三眼位图中眼球中心位移的幅度对所述活动角进行补偿具体为：获取所述第一眼位图、所述第二眼位图或第三眼位图中眼球中心不同程度位移形成的重叠成像，将所述重叠成像进行逆向平移以抵消所述位移对活动角的影响。
  8. 根据权利要求4所述的眼球活动度的评估方法，其特征在于，通过第一眼位图、第二眼位图或第三眼位图中角膜折射误差补偿对所述活动角进行补偿具体为：通过角膜折射误差补偿所补偿的角度与所述活动角成线性关系。
  9. 一种眼球活动度的评估***，其特征在于，包括：
    第一获取模块，用于在700-1200nm的近红外光光场中，在眼球前方位置拍摄获取用户平视前方的第一眼位图；
    第二获取模块，用于在眼球前方位置拍摄获取用户眼球沿待测方向运动到极限位置的第二眼位图和第三眼位图；
    图像处理模块，用于将所述第一眼位图分别与所述第二眼位图和第三眼位图进行对比，计算眼球活动度的活动角。
  10. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有至少一条程序代码，所述至少一条程序代码由处理器加载并执行以实现如权利要求1至8任一项所述的眼球活动的评估方法。
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