TWI632486B - Method for detecting and recording visual distortion - Google Patents

Abstract

The invention mainly provides a visual deformation detecting and recording method, which comprises the steps of: giving a subject a test pattern; the subject viewing the test pattern by his own vision, and viewing a self vision from the test graphic by his own vision. The graphic, the self-visual graphic has a visual shape variable compared with the test graphic; the subject draws his own visual graphic and adjusts his own visual graphic until the tester obtains the test graphic by viewing his own visual graphic by his own vision. Recording the amount of adjustment by the subject to adjust the visual pattern of the subject to the test pattern; and obtaining the actual data of the visual shape variable by calculating the adjustment amount; wherein the visual deformation detection recording method is controlled by computer, virtual reality One of the control or augmented reality controls is implemented; in addition, the present invention also provides another visual deformation detection recording method.

Description

Visual deformation detection recording method

The invention relates to a detection recording method, in particular to a method for detecting and recording a human visual shape variable.

The human eye is the window of a person's soul, used to view the rich scenery of the world. Like other mammalian eyes, the human eye has many uses. As a sensory organ, the eye responds to light and transmits a signal to the brain to produce vision. On the retina at the back end of the eye, there are rod cells and cone cells that can distinguish the color and shape of the external things and produce depth of field. The central area of the retina is called the macula, and the macula contains a large number of cone cells, cone cells and centers. Vision, color vision and shape sensory function are related. Rod cells are related to dark vision and peripheral vision. It is estimated that the human eye can distinguish about 10 million colors.

In current eye vision, the shape variables of visual deformation are more difficult to detect and record. Figure 1a is a schematic diagram illustrating a normal line pattern. Referring to FIG. 1a, a normal person will see a normal figure 10 in FIG. 1a with his healthy eyes. The normal figure 10 is a square figure consisting of a plurality of straight lines and horizontal lines including a plurality of squares. Fig. 1b is a schematic view for explaining a line pattern viewed by a person having visual distortion in Fig. 1a; Fig. 1c is a schematic view for explaining a line pattern viewed by a person having severe visual distortion in Fig. 1a . Referring to FIG. 1b and FIG. 1c, when a person with visual distortion views the normal figure shown in FIG. 1a with his own vision. At 10 o'clock, the visual deformation pattern 12 as shown in FIG. 1b is viewed. Although the circumference of the visual deformation pattern 12 is a normal straight straight line and a horizontal line, the middle of the visual deformation pattern 12 is a line of the crotch region, and the visual deformation pattern 12 is The normal pattern 10 already has a deformation compared to the normal pattern 10; when the situation of the visual distortion is more severe, the visual distortion pattern 14 as shown in Fig. 1c is seen, as can be seen from Fig. 1c, the pattern or object has been completely distorted. It can be seen from the above description of the visual deformation that a person with visual distortion cannot see the normal form of the figure or the object, thus causing inconvenience in life.

However, because the shape variables of visual deformation are only known to the parties themselves, when the party simply reflects to the physician or other person that the viewing of the figure or the object will distort the deformation, the physician or other person cannot clearly know the actual data of the visual shape variable of the party. This will cause inconvenience in communication between the two parties.

For the above reasons, how to know the actual data of the visual shape variable is a problem to be solved.

In view of the above disadvantages of the prior art, the main object of the present invention is to provide a visual deformation detecting and recording method, which comprises the steps of: giving a subject a test pattern; the subject viewing the test pattern by own vision, and by The self-vision visualizes a self-visual graphic from the test graphic. The self-visual graphic has a visual variable compared with the test graphic; the subject draws his own visual graphic and adjusts his visual image until the subject is visualized by his or her own vision. When viewing the visual image of the self, the test pattern is obtained; the adjustment amount of the subject's own visual pattern is adjusted to the test pattern; and the actual data of the visual shape variable is obtained by calculating the adjustment amount; The visual deformation detection recording method is implemented by one of computer control, virtual reality control or augmented reality control.

Furthermore, the visual deformation detecting and recording method of the present invention further includes the following steps: before the step of giving the subject a test pattern, the graphic of the fundus of the subject's eye is performed before the test pattern is given to the subject. Taking a picture to obtain a fundus pattern, and generating a complex prediction adjustment amount according to the fundus pattern; based on the test pattern, generating a plurality of prediction test patterns by the complex prediction adjustment amount; and giving the plurality of prediction test patterns to the subject, the subject Each of the plurality of predictive test patterns is viewed from the complex predictive test pattern by its own vision, and each of the complex predictive self-vision patterns has a visual shape variable compared to the test pattern; the subject selects from the complex prediction self-vision graphic The visual shape variable is a minimum predicting self-visual graphic; and a predictive test graphic corresponding to the predicted self-visual graphic having the minimum visual visual variable as a new version of the test graphic for the subject to view, draw and adjust.

Preferably, the test pattern and the self-vision pattern are lines including a plurality of line segments, and each of the plurality of line segments has two end points.

Preferably, the complex prediction test pattern and the complex prediction self-vision pattern are lines including a plurality of line segments, and each of the plurality of line segments has two end points.

Preferably, the subject adjusts the self-vision graphic to the test pattern by adjusting the two endpoints of each segment of the plurality of segments.

Preferably, the lines comprising the plurality of line segments constitute a geometric figure.

Preferably, the subject draws and adjusts the two endpoints of the plurality of line segments by one of a mouse, a hand-held remote controller or a hand-held sensor.

Preferably, the test pattern is a Morley corrugation.

Preferably, the predicted test pattern is a Morley corrugation.

Other objects, advantages and novel features of the invention will be apparent from

10‧‧‧Normal graphics

12, 14‧‧‧ visual deformation graphics

20‧‧‧ lines

22‧‧‧Visual deformation lines

30, 34‧‧‧ test graphics

32‧‧‧ Self visual graphics

301, 321‧‧ ‧ line segments

3011, 3211‧‧‧ endpoints

40‧‧‧First prediction test graph

42‧‧‧Second prediction test graphics

44‧‧‧ Third predictive test pattern

401, 421, 441‧‧ ‧ line segments

End points 4011, 4211, 4411‧‧

50‧‧‧First prediction of own visual graphics

52‧‧‧Second prediction of own visual graphics

54‧‧‧The third prediction of its own visual graphics

501, 521, 541‧‧ ‧ line segments

End points 5011, 5211, 5411‧‧

60, 64, 90‧‧‧ test graphics

62‧‧‧ Self visual graphics

Lines 601, 621, 641, 901‧‧

End points 6011, 6211, 6411, 9011‧‧

S10-S100‧‧‧Steps

The foregoing summary of the preferred embodiments of the invention, as well as For the purposes of illustrating the invention, various examples are now shown in the drawings. However, it should be understood that the invention is not limited to the precise arrangements and devices disclosed.

1a is a schematic view illustrating a normal line pattern; FIG. 1b is a schematic view illustrating a line pattern viewed by a person having visual distortion in FIG. 1a; and FIG. 1c is a view showing a line viewed in FIG. 1a by a person having severe visual distortion. 2a is a schematic diagram illustrating a test pattern of the present invention; FIG. 2b is a schematic view showing a pattern obtained by the subject of the present invention viewed from FIG. 2a; FIG. 3 is a view showing visual deformation detection according to an embodiment of the present invention; FIG. 4a is a schematic diagram illustrating a test pattern in an embodiment of the present invention; FIG. 4b is a schematic view showing a pattern obtained by the subject in FIG. 4a in an embodiment of the present invention; FIG. 4c is a schematic view A schematic diagram of the image obtained by the subject in the embodiment of the invention after adjusting the pattern of FIG. 4b to the test pattern; 5 is a flow chart illustrating a visual deformation detection recording method according to another embodiment of the present invention; FIG. 6a is a schematic diagram illustrating a first prediction test pattern in another embodiment of the present invention; and FIG. 6b is another embodiment of the present invention. A schematic diagram of a second prediction test pattern; FIG. 6c is a schematic diagram illustrating a third prediction test pattern in another embodiment of the present invention; and FIG. 7a is a first prediction example corresponding to the first prediction test pattern in another embodiment of the present invention; FIG. 7b is a schematic diagram illustrating a second predicted self-vision pattern corresponding to a second prediction test pattern in another embodiment of the present invention; FIG. 7c is a diagram illustrating a third prediction test pattern according to another embodiment of the present invention; FIG. 8a is a schematic diagram illustrating a test pattern in another embodiment of the present invention; FIG. 8b is a schematic view illustrating a pattern obtained by the subject in FIG. 8a in another embodiment of the present invention; FIG. A schematic diagram for adjusting the pattern of FIG. 8b to become a test pattern for explaining the subject in other embodiments of the present invention; and FIG. 9 is a view for explaining another embodiment of the present invention. A schematic diagram of the test pattern.

Reference will now be made in detail to the exemplary embodiments illustrated in the drawings All figures are represented by the same element symbols as the same or similar parts. Please note that these drawings are drawn in simplified form and are not drawn to exact scale.

Fig. 2a is a schematic view for explaining the test pattern of the present invention; Fig. 2b is a view for explaining the pattern obtained by the subject of the present invention when viewing Fig. 2a. Please refer to Figure 2a And in Fig. 2b, in the concept of the present invention, the subject is first given a line 20, and when the subject views the line 20 by his own vision, the visual deformation line 22 is viewed; at this time, the subject is allowed to draw The visually deformed line 22 is caused, and the subject is adjusted to adjust the visually deformed line 22 until the visually deformed line 22 becomes the line 20 when the subject is viewed by his own vision, while the visually deformed line 22 is recorded as the line 20 The amount of adjustment; finally, the actual data of the visual shape variable is obtained by calculating the adjustment amount. Since the simple line is inconvenient for the subject to adjust, in one embodiment of the present invention, the line is adjusted by the subject by a line including a plurality of line segments, and each of the plurality of line segments has two end points.

FIG. 3 is a flow chart for explaining a visual distortion detecting and recording method according to an embodiment of the present invention. Referring to FIG. 3, the visual distortion detecting and recording method according to an embodiment of the present invention includes steps S10-S50. Step S10 is: giving a test pattern to a test subject; step S20 is: the test subject viewing the test graphic by self vision. And viewing a self-visual graphic from the test graphic by self-vision; step S30 is: the subject draws and adjusts the self-vision graphic; step S40 is: recording the adjustment amount of the tester adjusting the self-vision graphic to the test graphic; And step S50 is: obtaining actual data of the visual shape variable by calculating the adjustment amount.

The embodiment of each step will now be described in detail. FIG. 4a is a schematic diagram for explaining a test pattern in an embodiment of the present invention; FIG. 4b is a schematic view for explaining the subject in an embodiment of the present invention. Fig. 4a is a schematic view for explaining a figure obtained by the subject in the embodiment of the present invention adjusting the figure of Fig. 4b into a test pattern. Referring to FIG. 4a and FIG. 4b, in step S10, a test pattern 30 is given to the subject, the test pattern 30 is a line composed of a plurality of line segments 301, and each of the plurality of line segments 301 has two end points 3011.

In step S20, the subject views the test pattern 30 by his own vision and views a self-vision graphic 32 as shown in Fig. 4b from the test pattern 30 by his own vision. The self-vision graphic 32 is also a line composed of a plurality of line segments 321 and each segment of the plurality of line segments 321 has two end points 3211. The self visual graphic 32 has a visually variable variable compared to the test graphic 30.

In step S30, the subject draws his own visual figure 32 and adjusts his own visual figure 31 until the subject obtains the test figure 34 as shown in FIG. 4c when viewing the self-vision figure 32 by his or her own vision. . The subject adjusts the self-vision graphic 32 by the two endpoints 3211 of the plurality of line segments 321 . In detail, the subject moves the two-point 3211 of the plurality of line segments 321 by left and right to adjust the self-vision pattern to Test pattern 34.

In step S40, the subject is recorded to adjust the self-vision pattern 32 to the adjustment amount of the test pattern 34 (also the amount of movement of the two end points 3211 of the plurality of line segments 321).

In step S50, the actual data of the subject's visual shape variable is obtained by calculating the adjustment of the self-vision pattern 32 to the adjustment amount of the test pattern 34 (also the movement amount of the two end points 3211 of the complex line segment 321).

FIG. 5 is a flow chart for explaining a visual distortion detecting and recording method according to another embodiment of the present invention. Referring to FIG. 5, the visual deformation detection recording method according to another embodiment of the present invention is further included in step S10-S100 before step S10, and step S60 is: before the test subject is given the test, the eye of the test subject is first The fundus is photographed to obtain a fundus pattern, and a complex predictor adjustment is generated based on the fundus pattern. Step S70 is: generating, according to the test pattern (for example, the test pattern 30 shown in FIG. 4a), a plurality of prediction test patterns by using the plurality of prediction adjustment amounts; and step S80 is: giving the plurality of prediction test patterns to the subject, being tested By own vision Observing a plurality of predicted self-visual graphics from the complex prediction test pattern, each of the complex prediction self-vision graphics has a visual shape variable compared to the test graphics; step S90 is: the subject predicts the self-vision graphics from the prediction Selecting a predicted self-vision graphic whose visual shape variable is a minimum value; and step S100 is: using a prediction test graphic corresponding to the predicted self-visual graphic with the visual shape variable as a minimum value as a new version of the test graphic for the subject to view, Draw and adjust.

Embodiments of each step of another embodiment of the present invention will now be described in detail. In step S60, before the test pattern is given to the subject, the fundus (retina and/or macular structure) of the subject's eye is graphically photographed to obtain a fundus pattern, and a complex predictor adjustment amount is generated based on the fundus pattern.

6a is a schematic diagram for explaining a first prediction test pattern in another embodiment of the present invention; FIG. 6b is a schematic diagram for explaining a second prediction test pattern in another embodiment of the present invention; FIG. 6c is a schematic diagram. To illustrate a third prediction test pattern in another embodiment of the present invention. Referring to FIG. 6a to FIG. 6c, in step S70: based on the test pattern (for example, the test pattern 30 shown in FIG. 4a), a plurality of prediction test patterns are generated by the complex prediction adjustment amount, for example, as shown in FIG. 6a. The first predictive test pattern 40 of the slightly deformed variable, the second predicted test pattern 42 having the medium-shaped variable shown in Fig. 6b, and the third predicted test pattern 44 having the severely shaped variable shown in Fig. 6c. The first prediction test pattern 40 is a line composed of a plurality of line segments 401, and each of the plurality of line segments 401 has two end points 4011; the second prediction test pattern 42 is a line composed of the plurality of line segments 421, and each of the plurality of line segments 421 There are two endpoints 4211; the third prediction test pattern 44 is a line formed by a plurality of line segments 441, and each segment of the plurality of line segments 441 has two endpoints 4411.

FIG. 7a is a schematic diagram for explaining a first predicted self-vision pattern corresponding to a first prediction test pattern in another embodiment of the present invention; FIG. 7b is a schematic diagram for explaining a second prediction in another embodiment of the present invention; The second predicted self-visual graphic of the test pattern; FIG. 7c is a schematic diagram for explaining a third predicted self-visual graphic corresponding to the third predicted test pattern in another embodiment of the present invention. Referring to FIG. 6a to FIG. 6c and FIG. 7a to FIG. 7c, in step S80, the first prediction test pattern 40, the second prediction test pattern 42, and the third prediction test pattern 44 are given to the subject, and the subject borrows The corresponding first predicted self visual graphic 50, the second predicted self visual graphic 52, and the third predicted self visual graphic are viewed from the first prediction test graphic 40, the second prediction test graphic 42, and the third prediction test graphic 44 by the self vision. 54 wherein each of the first predicted self visual graphic 50, the second predicted self visual graphic 52, and the third predicted self visual graphic 54 has a visually variable variable as compared to the test graphic 30 illustrated in FIG. 4a. Similarly, the first predicted self-vision graphic 50 is a line composed of a plurality of line segments 501, and each of the plurality of line segments 501 has two end points 5011; the second predicted self-vision pattern 52 is a line formed by the plurality of line segments 521, and plural Each segment of line segment 521 has two endpoints 5211; a third predicted self-vision graphic 54 is a line formed by a plurality of line segments 541, and each segment of the plurality of line segments 541 has two endpoints 5411. It should be understood that although in another embodiment of the present invention, the subject is given three predictive test patterns for viewing, in other embodiments, the subject may be given any number of predictive test patterns, such as three In the following (one or two) or more than three, the number of the complex prediction test patterns can be adjusted according to the degree of deformation of each prediction pattern.

In step S90, the subject selects the visual shape variable from the first predicted self visual pattern 50, the second predicted self visual graphic 52, and the third predicted self visual graphic 54 to a minimum value (with the test graphic 30 shown in FIG. 4a). Compared to a prediction of its own visual graphics; in this embodiment Among them, the smallest visual shape variable is the second predicted self visual pattern 52.

In step S100, the predicted test pattern 42 corresponding to the predicted self-vision pattern 52 is used as a new version of the test pattern for the subject to view, draw, and adjust (i.e., steps S10-S50 shown in FIG. 3 are performed).

Another embodiment of the present invention predicts the degree of deformation of the subject by first predicting the test pattern for the subject to view, and allowing the subject to select the graphic with the smallest visual shape variable as the new test pattern. Perform visual deformation detection recording. This approach saves the subject's time to adjust the graphics (because the new test graphics have minimal visual variables).

In the above two embodiments of the present invention, the line including the plurality of line segments is used to allow the subject to perform visual deformation detection recording, but it should be understood that in other embodiments of the present invention, the measured condition may also be provided. The more complex graphics are used for visual deformation detection recording, so that the actual data of the subject's visual deformation can be further understood, for example, a geometrical figure composed of lines including a plurality of line segments can be provided. Figure 8a is a schematic view for explaining the structure of a test pattern in another embodiment of the present invention; Figure 8b is a schematic view for explaining the pattern structure obtained by the subject in the other embodiment of the present invention when viewing the Figure 8a; Figure 8c It is a schematic diagram for explaining the structure in which the subject in the other embodiment of the present invention adjusts the graph of FIG. 8b to become a test pattern. Referring to FIG. 8a to FIG. 8c, the subject can be given a test pattern 60. The test pattern 60 is a geometric figure composed of a plurality of line segments 601 (shown as a square or other geometric shapes), and each of the plurality of line segments 601 One segment has two endpoints 6011. Next, the subject is allowed to view the test pattern 60 by his own vision, and a self-vision pattern 62 as shown in FIG. 8b is viewed from the test pattern 60 by his own vision. The self-vision graphic 62 is also a line composed of a plurality of line segments 621, and each of the plurality of line segments 621 has two end points 6211. The self visual graphic 62 has a visually variable variable compared to the test graphic 60. most Then, the subject is allowed to draw his own visual figure 62 and adjust his own visual figure 62 until the tester 64 sees the test figure 64 as shown in FIG. 8c when viewing the self-vision graphic 62 by his own vision. Wherein, the test pattern 64 is also a line composed of a plurality of line segments 641, and each of the plurality of line segments 641 has two end points 6411. It should be understood that the geometry formed by the plurality of line segments can also be applied to another embodiment of the present invention. In other words, based on the test pattern 60, the complex prediction test pattern can be generated by predicting the adjustment amount to allow the test to be performed. The following steps are the same as the other embodiment of the present invention, and details are not described herein again.

Figure 9 is a schematic view for explaining the structure of a test pattern in another embodiment of the present invention. Please refer to FIG. 9. FIG. 9 shows a more complicated test pattern 90. The test pattern 90 is a geometric figure composed of a plurality of line segments 901 (shown as a square or other geometric shapes), and each of the plurality of line segments 901 One segment has two endpoints 9011. It is worth mentioning that the complex segment 901 forms another geometric figure (shown as a square or other geometric shape) in the middle of the test pattern 90, so that the test pattern can be The two square geometric shapes in 90 are tested by the subject. Since the test pattern 90 has more line segments 901 and endpoints 9011, the measured results are more accurate. It should be understood that the visual deformation detection recording method performed by using the test pattern 90 is the same as the step S10 to step S50 shown in FIG. 3 of the present invention, and details are not described herein. In addition, based on the test pattern 90, the complex prediction test pattern can be generated by predicting the adjustment amount for the subject to view, because the subsequent steps are the same as the other embodiment of the present invention, and the other side will not be described herein. All of the above embodiments of the visual distortion detection recording method of the present invention can be controlled by computer control, virtual reality (VR) control or Augmented Reality (AR) control. According to the implementation, in other words, the subject can be displayed by computer screen, mouse control, graphic projection display, handheld remote control or hand-held sense The two endpoints of the complex line segment are drawn and adjusted by the control of the device, and the adjustment amount is transmitted to a processor for calculation processing. Furthermore, in the above embodiments of the present invention, the test pattern or the prediction test pattern may be a Moire pattern in the prior art, and the Moire line is an interference image generated by overlapping the fence-like stripes. Because of its overlapping and regularity, the test graphics/predictive test graphics can be overlapped with their own visual graphics/predictive visual graphics to more accurately calculate the actual data of the visual shape variables.

It can be seen from the above that the present invention provides a visual deformation detection recording method which effectively calculates the actual data of the visual shape variable of the subject using the segmented line.

In describing a representative example of the invention, the present specification has been presented as a specific sequence of steps of the method and/or procedure of the invention. However, to some extent, the method or program does not rely on the specific order of steps set forth herein, and the method or program should not be limited to the particular order of the steps described. As will be appreciated by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in this specification should not be construed as limiting the scope of the claims. In addition, the scope of the patent application of the method and/or procedure of the present invention should not be limited to the performance of the steps in the order presented, and those skilled in the art can immediately understand that the order can be changed and still maintain the spirit of the present invention. Within the scope.

Those skilled in the art should be aware that changes can be made to the above examples without departing from the broad inventive concepts. Therefore, it is understood that the invention is not limited to the specific examples of the invention, and is intended to cover the modifications of the invention and the scope of the invention as defined by the appended claims.

Claims (6)

A visual deformation detecting and recording method comprises the steps of: giving a subject a test pattern; the subject viewing the test pattern by his own vision, and viewing a self-visual graphic from the test graphic by his own vision, The self-vision graphic has a visual shape variable compared to the test graphic; the subject draws the self-vision graphic and adjusts the self-vision graphic until the subject views the self-vision graphic by his or her own vision Obtaining the test pattern; recording the adjustment of the self-vision pattern to the adjustment amount of the test pattern; and obtaining the actual data of the visual shape variable by calculating the adjustment amount; wherein the visual deformation detection The recording method is implemented by one of computer control, virtual reality control or augmented reality control, wherein the test pattern and the self-vision graphic are lines including a plurality of line segments, each segment of the line segments Having two endpoints, and the subject adjusts the self-vision graphic to the measurement by adjusting the two endpoints of each segment of the segment a graphic, wherein, before the step of administering the test pattern to the subject, the method further comprises the step of: performing a graphic photograph of the fundus of the subject's eye before giving the test pattern to the subject to obtain a graphic a fundus graphic, and generating a complex prediction adjustment amount according to the fundus graphic; and generating, by the test pattern, a plurality of prediction test patterns by using the prediction adjustment amount; And giving the predicted test pattern to the subject, the subject viewing the corresponding plurality of predicted self-vision patterns from the predicted test patterns by self-vision, and predicting each of the self-vision patterns and the test pattern Comparing to the visual shape variable; the subject selects the predicted self visual image whose visual shape variable is the minimum value from the predicted self visual patterns; and the prediction itself that minimizes the visual shape variable A predicted test pattern corresponding to the visual pattern is used as a new version of the test pattern for the subject to view, draw, and adjust. The visual distortion detection recording method as described in claim 1, wherein the prediction test patterns and the prediction self-vision patterns are lines including a plurality of line segments, each of the line segments having two end points. The visual distortion detecting recording method of claim 1, wherein the line including the line segments constitutes a geometric figure. The visual distortion detecting and recording method according to any one of the preceding claims, wherein the subject draws and adjusts by one of a mouse, a hand-held remote controller or a hand-held sensor The two endpoints of the line segments. The visual distortion detecting recording method according to claim 1, wherein the test pattern is a Morley corrugation. The visual distortion detecting recording method of claim 1, wherein the predictive test pattern is a Morley corrugation.