TWI429901B - Method and system for defect detection of 3d optical film - Google Patents

Description

Method and system for detecting flaw of three-dimensional optical film

The present invention relates to an automated optical inspection (AOI), and more particularly to a method and system for detecting defects of a 3D optical film.

The existing optical film detection technology is mostly for detecting products whose surface has no texture characteristics. Referring to FIG. 1 , taking a polarized film having no surface texture as an example, according to the characteristics of the color images of the corresponding images 11 and 12 of the polarizer, it is possible to directly determine which one has flaws; Further, the polarizer corresponding to the image 11 having a small color variation is a defect-free polarizer, and the polarizer corresponding to the image 12 having a large color variation is a polarizer having a flaw.

However, the three-dimensional optical film belongs to a product having a structural texture on the surface, and therefore it is impossible to perform flaw detection using the characteristics of its corresponding image in the color space.

Accordingly, it is an object of the present invention to provide a flaw detection method for a three-dimensional optical film.

Therefore, the method for detecting the flaw of the three-dimensional optical film of the present invention is performed by using a processing unit and an image capturing unit for capturing a to-be-detected image corresponding to a three-dimensional optical film to be detected; The method consists of the following steps:

(A) receiving the image to be detected;

(B) determining, according to at least one region of the image to be detected, a plurality of first projection amounts of the region in a first direction;

(C) determining, according to the first projection amount of the region obtained in the step (B), a first detection parameter corresponding to the region;

(D) determining, according to the first detection parameter corresponding to the region, the step (C), determining whether the region in the image to be detected has flaws;

(E) Output the judgment result of the step (D).

Another object of the present invention is to provide a flaw detection system for a three-dimensional optical film.

Thus, the flaw detection system of the three-dimensional optical film of the present invention comprises an image capture unit and a processing unit. The image capturing unit is configured to capture a to-be-detected image corresponding to a three-dimensional optical film to be detected. The processing unit is configured to: receive the image to be detected; and determine, according to at least one region of the image to be detected, a plurality of first projection amounts of the region in a first direction; according to the first of the regions Deriving a first 瑕疵 detection parameter corresponding to the area; and determining whether the area in the image to be detected has 瑕疵 according to the first 瑕疵 detection parameter corresponding to the area, and outputting the determination result.

The invention has the effect that the three-dimensional optical film having the texture property can be detected by the first flaw detection parameter obtained from the first projection amount of the region in the image to be detected.

The above and other technical contents, features and advantages of the present invention will be apparent from the following detailed description of the preferred embodiments.

Referring to FIG. 2, a preferred embodiment of the flaw detection system 2 of the three-dimensional optical film of the present invention comprises an optical lens 21, an image capture unit 22, and a processing unit 23. The image capturing unit 22 is configured to capture an image corresponding to a three-dimensional optical film under the optical lens 21; the processing unit 23 is configured to perform flaw detection according to the image corresponding to the three-dimensional optical film.

The steps performed by the processing unit 23 will be described below in conjunction with a preferred embodiment of the method for detecting flaws in the three-dimensional optical film of the present invention. The detection method of the three-dimensional optical film is divided into a system initialization phase and a system detection phase.

[System initialization phase]

First, referring to FIG. 2 to FIG. 5, the image capturing unit 22 captures a first training image 31 corresponding to a flawless three-dimensional optical film, wherein the first training image 31 has the same as shown in FIG. The structural texture properties shown.

Then, the processing unit 23 performs the following steps to obtain an optimum area size.

In step 41, the processing unit 23 receives the first training image 31.

In step 42, the processing unit 23 performs a binarization process on the first training image 31 to obtain the binarized first training image 31, wherein the first training image 31 is binarized. Is a binary image.

In step 43, the processing unit 23 obtains at least one horizontal texture period and at least one vertical texture period based on the binarized first training image 31.

The horizontal texture period and the vertical texture period are further described in conjunction with a binary example image 51 shown in FIG. 5; wherein the binary example image 51 includes a plurality of pixels 511 whose binary value is 0. And a plurality of pixels 512 whose binary value is 1. In the preferred embodiment, the processing unit 23 obtains the horizontal texture period and the vertical texture period according to the calculation results of the equations (1) to (2).

Let the size of the binary example image 51 be represented by m × n ; and let the two-dimensional coordinates of each of the pixels 511, 512 in the binary sample image 51 be represented by ( x , y ), the binary example image 51 The two-dimensional coordinates of the pixel 511 in the upper left corner are (1, 1), and the two-dimensional coordinates of the pixel 511 in the lower right corner are ( m , n ); P ( x , y ) represents its two-dimensional coordinates ( The binary values of pixels 511 and 512 of x , y ).

Where i = 1, 2, ..., m -1, j = 1, 2, ..., n - 1.

For convenience of explanation, the calculation results of the equations (1) to (2) are respectively illustrated by a first graph 52 and a second graph 53; from the first graph 52, SUM _{H _ diff} ( 4) = SUM _{H _ diff} (8) = SUM _{H _ diff} (12) = 0, the corresponding physical meaning is: the repetition period of the texture of the binary example image 51 in the horizontal direction is 4, 8, 12; Ground, from the second graph 53, it can be seen that SUM _{V _ diff} (4) = SUM _{V _ diff} (8) = SUM _{V _ diff} (12) = 0, and its corresponding physical meaning is: the binary example image The repetition period of the texture in the vertical direction of 51 is 4, 8, and 12. Let the horizontal texture period be represented by H _ period and the vertical texture period be represented by V _ period . In this example, three horizontal texture periods and three vertical texture periods are obtained; that is, H _ period = 4, 8, 12, V _ period = 4, 8, 12.

More generally speaking, as long as the valleys in the first graph 52 and the second graph 53 are respectively found, a horizontal texture period ( H _ period ) and a vertical texture period ( V _ period ) can be obtained; in other words According to the calculation results of equations (1) to (2), with a preset first threshold value (expressed as thr ₁ ) and a second threshold value (expressed as thr ₂ ), H _ period and V _ period ; wherein the relationship between SUM _{H _ diff} ( H _ period ) and thr ₁ , and SUM _{V _ diff} ( V _ period ) and thr ₂ is further expressed as equations (3) to (4).

SUM _{H_diff} ( H _ period )< thr ₁ ...................................(3)

SUM _{V _ diff} ( V _ period )< thr ₂ ....................................(4)

In step 44, the processing unit 23 determines the optimal region size based on the horizontal texture period and the vertical texture period. Let the optimum region size be represented by w × h ; in the preferred embodiment, the optimal region size is determined by the minimum horizontal texture period and the minimum vertical texture period; that is, w =min( H _ Period ), h =min( V _ period ).

Then, referring to FIG. 2, FIG. 3 and FIG. 6, the image capturing unit 22 captures a second training image 32 corresponding to a three-dimensional optical film having a defect, and the processing unit 23 then performs the following steps to obtain a first A detection parameter upper limit value, a first 瑕疵 detection parameter lower limit value, a second 瑕疵 detection parameter upper limit value, and a second 瑕疵 detection parameter lower limit value.

In step 61, the processing unit 23 receives the second training image 32.

In step 62, the processing unit 23 performs binarization processing on the second training image 32 to obtain the binarized second training image 32.

In step 63, the processing unit 23 divides the binarized second training image 32 into a plurality of training regions according to the optimal region size ( w × h ) obtained in advance; wherein the size of each training region Equal to the optimal area size.

In step 64, the processing unit 23 obtains a plurality of first training projection amounts in a first direction of each training region according to the training regions in the binarized second training image 32, and a plurality of second training projections in a second direction. In the preferred embodiment, the first direction is a horizontal direction, the second direction is a vertical direction, and the second direction is perpendicular to the first direction; the first and second trainings of each training area The projection amount is calculated using equations (5) to (6).

Wherein, for each training region, Hp ( y ) represents the first training projection amount of the training region, and Vp ( x ) represents the second training projection amount of the training region; y =1, 2, .. , h , x =1, 2,..., w ; P ( x , y ) represents the binary value of the pixel whose two-dimensional coordinates are ( x , y ) in the training region.

In step 65, the processing unit 23 calculates a first training standard deviation corresponding to each training region according to the first training projection amount of each training region, and the second training projection amount, and a first The second training standard deviation; its calculation is as shown in equations (7) ~ (8).

Wherein, for each training area, Hp _ Std corresponding to the first representative of the standard training training zone difference, Vp_Std corresponding to the second training on behalf of the standard training area difference; Hp _avg training on behalf of those of the first region An average of a training projection amount, Vp _avg representing an average of the second training projections of the training region.

In step 66, the processing unit 23 determines the upper and lower limit values of the first detection parameter according to the first training standard deviation corresponding to the training regions and the second training standard deviation respectively. The second parameter detects the upper and lower limits of the parameter; the calculation is as shown in equations (9)~(12).

Hp _ thr _u = Hp _ Std _avg + k × Hp _ Std _std ...............................(9)

Hp _ thr _l = Hp _ Std _avg - k × Hp _ Std _std ...............................(10)

Vp _ thr _u = Vp _ Std _avg + k × Vp _ Std _std ................................(11)

Vp _ thr _l = Vp _ Std _avg - k × Vp _ Std _std .................................(12)

Where Hp _ thr _u represents the first 瑕疵 detection parameter upper limit value, Hp _ Std _avg represents an average value of the first training standard deviations, and Hp _ Std _std represents a standard deviation of the first training standard deviations Hp _ thr _l represents the first 瑕疵 detection parameter lower limit value, Vp _ thr _u represents the second 瑕疵 detection parameter upper limit value, Vp _ Std _avg represents an average value of the second training standard deviation, Vp _ Std _std represents a standard deviation of the second training standard deviation, Vp _ thr ₁ represents the second 瑕疵 detection parameter lower limit value, and k is a preset constant. In the preferred embodiment, k = 3.

[System Detection Phase]

Referring to FIG. 2 and FIG. 7 , after the system initialization phase is completed, the optimum region size ( w × h ) obtained in advance, the first detection parameter upper and lower limit values ( Hp _ thr _u , Hp) _thr ₁ ), and the upper and lower limit values ( Vp _ thr _u , Vp _ thr ₁ ) of the second 瑕疵 detection parameter are applied to the 瑕疵 detection of the three-dimensional optical film.

The image capturing unit 22 continuously captures an image to be detected corresponding to the three-dimensional optical film to be detected.

In step 71, the processing unit 23 receives an image to be detected.

In step 72, the processing unit 23 performs binarization processing on the image to be detected to obtain a binarized image to be detected.

In step 73, the processing unit 23 divides the binarized image to be detected into a plurality of regions according to the optimal region size ( w × h ); wherein the size of each region is equal to the optimal region size.

In step 74, the processing unit 23 obtains a plurality of first projection amounts of each region in the first direction (horizontal direction) according to the binarized regions in the image to be detected, and A plurality of second projection amounts in the second direction (vertical direction); the calculation is similar to the equations (5) to (6), and therefore will not be described again.

In step 75, the processing unit 23 calculates a first detection parameter (indicated by H _d ) corresponding to each region according to the first projection amounts of each region and the second projection amounts, and a second flaw detection parameter (expressed in V _d); in the present preferred embodiment, the system processing unit 23 calculates a first standard deviation of each region in accordance with such an amount as corresponding to a first projection in the region of the First detecting parameters, and calculating a second standard deviation according to the second projection amounts of each region as the second chirp detection parameter corresponding to the region, the calculation is similar to the equations (7)~(8) Therefore, it will not be repeated.

In step 76, the processing unit 23 cooperates with the first detection parameter and the second detection parameter corresponding to each area, and cooperates with the upper and lower limit values ( Hp_thr _u , Hp_thr _l ) of the first detection parameter. And the second and second detection parameter upper and lower limit values ( Vp_thr _u , Vp_thr _l ) to determine whether each region in the image to be detected has flaws. Wherein, for each region, if any one of the first detection parameter and the second detection parameter does not conform to the relationship (11) to (12), it represents that the region has 瑕疵; otherwise, represents the region For innocent.

Hp_thr _l < H _d < Hp_thr _u ......................................(11)

Vp_thr _l < V _d < Vp_thr _u ........................................(12)

In step 77, the processing unit 23 outputs the result of the determination of step 76, that is, whether the regions have detection results of 瑕疵; then, returning to step 71 to continue receiving the three-dimensional optical film corresponding to the next (next) to be detected. The next image to be tested.

It is worth mentioning that, by the judgment result of the step 76, the proportion of the 瑕疵 region in the three-dimensional optical film to be detected can be known; further, the erection position of the optical lens 21 of the 瑕疵 detection system 2 of the three-dimensional optical film is It is known that the geometrical correspondence between the image to be detected and the three-dimensional optical film to be detected is also known. Therefore, the detection result of the regions in the image to be detected can be correspondingly known to the three-dimensional to be detected. The relevant position in the optical film where enthalpy occurs.

In summary, the three-dimensional optical film having the texture property can be performed by receiving the first and second detection parameters corresponding to the regions in the image to be detected corresponding to the three-dimensional optical film to be detected.瑕疵 detection; further, matching the pre-determined optimal region size, the first 瑕疵 detection parameter upper and lower limits, and the second 瑕疵 detection parameter upper and lower limits, may be three-dimensional with texture characteristics The optical film is subjected to a fully automatic flaw detection, so that the object of the present invention can be achieved.

The above is only the preferred embodiment of the present invention, and the scope of the invention is not limited thereto, that is, the simple equivalent changes and modifications made by the scope of the invention and the description of the invention are All remain within the scope of the invention patent.

2‧‧‧Three-dimensional optical film flaw detection system

21‧‧‧Optical lens

22‧‧‧Image capture unit

23‧‧‧Processing unit

31‧‧‧First training image

32‧‧‧Second training image

41~44‧‧‧Steps

51‧‧‧ binary sample image

511‧‧ ‧ pixels

512‧‧ ‧ pixels

52‧‧‧First graph

53‧‧‧Second graph

61~66‧‧‧Steps

71~77‧‧‧Steps

Figure 1 is a schematic view showing a flawless polarizer and a polarizer having a cymbal, respectively corresponding to the image;

Figure 2 is a block diagram showing a preferred embodiment of the flaw detection system of the three-dimensional optical film of the present invention;

Figure 3 is a schematic view showing a first training image corresponding to a flawless three-dimensional optical film, and a second training image corresponding to a three-dimensional optical film having a flaw;

4 is a flow chart showing the steps for determining an optimum region size in a system initialization phase of a preferred embodiment of the flaw detection method of the three-dimensional optical film of the present invention;

Figure 5 is a schematic diagram showing a binary example image, a first graph, and a second graph;

6 is a flow chart for illustrating a first flaw detection parameter upper limit value, a first flaw detection parameter lower limit value, and a second flaw detection parameter upper limit value in the system initialization phase, and a second step of detecting a lower limit of the parameter; and

Figure 7 is a flow chart showing the steps involved in the system detection phase of the preferred embodiment of the flaw detection method of the three-dimensional optical film of the present invention.

71~77. . . step

Claims (8)

A method for detecting a flaw of a three-dimensional optical film is performed by using a processing unit coupled to an image capturing unit for capturing a to-be-detected image corresponding to a three-dimensional optical film to be detected, the method comprising the following Step: (A) receiving the image to be detected; (B) determining a plurality of first projection amounts of the region in a first direction according to at least one region of the image to be detected, wherein step (B) includes The following sub-steps: (b-1) binarizing the image to be detected to obtain a binarized image to be detected; and (b-2) binarizing the region in the image to be detected And determining the first projection amount of the region, wherein the step (b-2) comprises the following sub-steps: (b-2-1) binarizing the to-be-contained according to a pre-determined optimal region size The detection image is divided into a plurality of regions; and (b-2-2) for each region, the first projection amount of the region is obtained according to a plurality of binary values corresponding to the plurality of pixels in the region respectively (C) the first shot of the area as determined by step (B) Amount determined corresponding to a region of the first fault detection parameter; (D) of the said first region corresponding to the determined in accordance with step (C) The detection parameter determines whether the area in the image to be detected has flaws; and (E) the judgment result of the output step (D). According to the method for detecting a three-dimensional optical film according to claim 1, the image capturing unit is further configured to capture a first training image corresponding to a flawless three-dimensional optical film, the method further comprising the step ( A) the following steps: (F) receiving the first training image; (G) binarizing the first training image to obtain the binarized first training image; (H) according to the binary value The first training image is determined to obtain at least one horizontal texture period, and at least one vertical texture period; and (I) determining the optimal region according to the horizontal texture period and the vertical texture period obtained according to step (H) size. The method for detecting a flaw of a three-dimensional optical film according to claim 1, wherein the step (C) calculates a first standard deviation based on the first projection amounts of the region as the corresponding to the region The first test parameter. The method for detecting a flaw of a three-dimensional optical film according to claim 3, wherein the step (B) further determines a plurality of second projection amounts of the region in a second direction, wherein the second orientation system Vertical to the first direction; wherein step (C) is further based on the second projections of the region Calculating a second standard deviation as a second detection parameter corresponding to the region; wherein, step (D) is the first detection parameter corresponding to the region determined according to step (C) and the The second detection parameter determines whether the area in the image to be detected has flaws. According to the method for detecting a three-dimensional optical film according to claim 4, the image capturing unit is further configured to capture a second training image corresponding to a three-dimensional optical film having a flaw, the method further comprising the step ( A) the following steps: (J) receiving the second training image; (K) binarizing the second training image to obtain the binarized second training image; (L) according to the binary value a plurality of training regions in the second training image, obtaining a plurality of first training projections in the first direction of each training region, and a plurality of second training projections in the second direction And (M) calculating, according to the first training projection amount of each training region determined in step (L), and the second training projection amount, calculating a first training standard deviation corresponding to each training region And a second training standard deviation; (N) determining the first training standard deviation corresponding to the training regions according to the step (M), and the second training standard deviation, obtaining a first A test parameter upper limit value, a first flaw detection The parameter lower limit value, a second 瑕疵 detection parameter upper limit value, and a second 瑕疵 detection parameter lower limit value. The method for detecting a flaw of a three-dimensional optical film according to claim 5, wherein the step (N) determines the upper limit value of the first flaw detection parameter and the lower limit of the first flaw detection parameter by using the following formula The value, the second 瑕疵 detection parameter upper limit value, and the second 瑕疵 detection parameter lower limit value: Hp _ thr _u = Hp _ Std _avg + k × Hp _ Std _std ; Hp _ thr _l = Hp _ Std _avg - k × Hp _ Std _std ; Vp _ thr _u = Vp _ Std _avg + k × Vp _ Std _std ; and Vp _ thr _l = Vp _ Std _avg - k × Vp _ Std _std ; wherein Hp _ thr _u represents a first fault detection parameter value, a mean value Hp _ Std _avg training on behalf of such a first standard deviation, a standard Hp _ Std _std training on behalf of such a first standard deviation of the difference, Hp _ thr _l representing the second A detection parameter lower limit value, Vp _ thr _u represents the second 瑕疵 detection parameter upper limit value, Vp _ Std _avg represents an average value of the second training standard deviations, and Vp _ Std _std represents the second training One standard deviation of the standard deviation, Vp _ thr _l represents the lower limit of the second 瑕疵 detection parameter, k is a Preset constant. The method for detecting a flaw of a three-dimensional optical film according to claim 5, wherein the step (D) determines the first flaw detection parameter corresponding to the region and the second flaw detection according to the step (C) a parameter, and matching the first upper detection parameter upper limit value obtained in advance, the first The detection parameter lower limit value, the second detection parameter upper limit value, and the second detection parameter lower limit value are used to determine whether the area in the image to be detected has flaws. A flaw detection system for a three-dimensional optical film, comprising: an image capture unit for capturing a to-be-detected image corresponding to a three-dimensional optical film to be detected; and a processing unit for: receiving the image to be detected And binarizing the image to be detected to obtain a binarized image to be detected; dividing the binarized image to be detected into a plurality of regions according to a predetermined optimal region size; An area, according to a plurality of binary values corresponding to the plurality of pixels in the area, obtaining a plurality of first projection amounts of the area in a first direction; according to the first projection amount of the area, Obtaining a first detection parameter corresponding to the region; and determining, according to the first detection parameter corresponding to the region, whether the region in the image to be detected has flaws, and outputting the determination result.