CN104655403A - Luminance uniformity test method of dot-matrix light source - Google Patents
Luminance uniformity test method of dot-matrix light source Download PDFInfo
- Publication number
- CN104655403A CN104655403A CN201410044024.7A CN201410044024A CN104655403A CN 104655403 A CN104655403 A CN 104655403A CN 201410044024 A CN201410044024 A CN 201410044024A CN 104655403 A CN104655403 A CN 104655403A
- Authority
- CN
- China
- Prior art keywords
- image
- array
- point
- value
- uniformity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Abstract
The invention discloses a luminance uniformity test method of a dot-matrix light source, and relates to the technical fields of display, illumination and image processing. According to the luminance uniformity test method, the luminance uniformity is divided into brightness uniformity and distribution uniformity; the luminance uniformity of the dot-matrix light source is evaluated through the brightness uniformity, the distribution uniformity and the sum of the brightness uniformity and the distribution uniformity; in the testing process, image geometric distortion is corrected; the dot-matrix structure is analyzed, and the non-light-emitting area is excluded from the evaluation range. Compared with the existing test method, the luminance uniformity test method is more comprehensive, objective, accurate, effective, direct, simple and convenient.
Description
Technical field
The present invention relates to display, lighting source and Computer Image Processing field, especially relate to the method for testing of array light source.
Background technology
Array light source refer to by row with the set of multiple active illuminating points of row ordered arrangement, the type of device of light source comprises LCD, LED, FED and PDP etc.Along with the fast development of infotech, array light source has been widely used in the terminal of all kinds of multimedia equipment.It can be used as lighting source and backlight, also may be used for the screen showing the various information such as character, figure and video.The brightness uniformity of array light source affects its illumination or key factor of display performance, is therefore necessary very much to propose effective method of testing to the brightness uniformity of light source, for the production of related device and research and development provide guidance.
Current employing method of testing mainly adopts brightness instrument to randomly draw some sampled points to array light source and tests its brightness value, then final assessment result is obtained by certain algorithm, this method has one-sidedness, and each measurement can only obtain the data of a sampled point, obtain test result to need repeatedly to regulate testing tool, consuming time more.Have report to be obtained the monochrome information of lattice pixels by sensor, combining image treatment technology and Principle of Statistics, fit to normal distribution curve by the grey level histogram of pixel, utilizes standard deviation to evaluate brightness uniformity.The luminance picture also having report to propose sensor obtains is divided into some subregions, calculate all subregion based on HVS(human-eye visual characteristic) the brightness factor, the locus Summing Factor grain details factor, by the feature of these factors as the evaluating of subregion, then evaluate the brightness uniformity of light source by the dispersion degree value of all subregion parameter.But above method is all directly test the image obtained, do not correct taking the piecture geometry fault caused; Do not distinguish luminous point and non-luminous region, those non-luminous regions that should not participate in evaluating also are included in range of value yet; Further, or be a test brightness homogeneity, or only test distributing homogeneity, there is one-sidedness, do not evaluate uniformity of luminance all sidedly; Above deficiency causes the evaluation of array light source uniformity of luminance comprehensive not, accurate.
Summary of the invention
The object of this invention is to provide a kind of comprehensively, the method for test point array light source uniformity of luminance exactly.
For achieving the above object, the present invention is divided into brightness uniformity and distributing homogeneity uniformity of luminance, respectively with the uniformity of luminance of brightness uniformity, distributing homogeneity evaluation point array light source from different perspectives, the uniformity of luminance of comprehensive evaluation array light source is carried out by brightness uniformity and distributing homogeneity sum, and in test process, piecture geometry fault is corrected, non-luminous region is excluded range of value, the following scheme of concrete employing:
With taking pictures, capture video intercepts video image again or read the mode acquisition point array light source luminescent image having preserved image; In the image obtained, choose region to be tested, region to be tested can be any one shape, for easy to operate, can be rectangle; Generate test pattern; Read the gray-scale value of each pixel in described test pattern; Setting gray threshold, opens speck and background segment; Dot matrix distributed architecture, array point shape classification and characteristic parameter thereof are set, obtain array dot image at test pattern I; Add up pixel quantity that single array dot image comprises as array point area Sp, add up each array dot image comprise the quantity of speck pixel as array point speck total area Se, if the ratio of Se and the Sp of certain array point is greater than setting value (such as 0.3), then judge that this array point is as effective light spot, otherwise be considered as invalid hot spot; Calculate brightness uniformity and the distributing homogeneity of described effective light spot, the computing formula of brightness uniformity is:
Wherein, γ
1, γ
2..., γ
nthe average gray of each described effective light spot, γ
0the average gray of all described effective light spots, s
γgrey scale deviation, γ be less than 1 and be greater than 0 numerical value, for weighing brightness uniformity,
γmore close to 1, illustrate that the brightness of hot spot is more even,
γmore close to 0, illustrate that the brightness uniformity of hot spot is poorer;
The computing formula of distributing homogeneity is:
Wherein, β
1, β
2..., β
nafter photo being divided into equably n region, the hot spot number in each region, β
0the mean value of regional hot spot number, s
βhot spot number standard deviation,
βbe one be less than 1 and be greater than the numerical value of 0, for weighing the numerical value of brightness uniformity,
βmore close to 1, illustrate that the distribution of hot spot is more even;
βmore close to 0, illustrate that the distributing homogeneity of hot spot is poorer;
Calculate β and γ sum larger, β and γ sum is larger, illustrates that the homogeneity of light source is better;
Image and result of calculation are preserved, or exports display to, also can export other computer for further processing to.
The further scheme of the present invention is, after choosing region to be tested, carries out geometry deformity correction, regeneration test pattern to the image in described region to be tested in the image obtained.
After judgement effective light spot, also the image in effective light spot, background and non-test region is used different colours respectively, intuitively show with composograph, automatically processed by manual observation, judgement, selection or computing machine, choose result to lattice parameter, Iamge Segmentation and hot spot to optimize and revise further, obtain more accurate result.
Another further scheme of the present invention is, calculate dot matrix distributed architecture, array point shape classification and characteristic parameter thereof, obtain the step of array image specifically to adopt with the following method: according to the true form of array point (as circle, oval, square, rectangle and arbitrary polygon) and characteristic parameter (as the length of side and radius etc.) shape classification and the characteristic parameter thereof of array point in test pattern are tentatively set, sketch the contours of single array dot image, finely tune array point patterns parameter again, the characteristic parameter of the principle search optimum of maximal value should be obtained by cross correlation value r, finally determine the shape of single array point,
The computing formula of described r is
Wherein, P is the set of all sub-pixel points of topography, and I is the set of all sub-pixel points corresponding with P coordinate position in test pattern, I
ijkbe the gray-scale value of the sub-pixel point of (i, j, k) for image coordinate in I, I
afor I
ijkmean value, P
ijkbe the gray-scale value of the sub-pixel point of (i, j, k) for image coordinate in P, P
afor P
ijkmean value;
In test pattern, a selected array point is as staring array point, with staring array dot center coordinate for initial point, calculates lattice parameter, draw the coordinate of each array point according to the relative position of each array point and distance; Centered by each array point coordinate, dilation operation is carried out by the shape of single array point in position, obtains array image.
Another further scheme of the present invention is, utilize gray scale to fluctuate allowable value to judge whether grey scale change is caused by noise, concrete scheme is, setting gradation of image fluctuation allowable value Tc; If certain pixel is less than Tc with the gray scale difference of contiguous 8 pixels, then judging that grey scale change is caused by noise, is the gray-scale value of this pixel with the gray scale maximal value in contiguous 8 pixels; To there is the eight connectivity path that at least one grey scale change is less than Tc between the border of two described specks if having, then two specks are merged into a speck, all pixels on communication path are also under the jurisdiction of this speck.
Owing to adopting such scheme, the present invention compared with prior art can bring following technique effect: adopt and carry out geometry deformity correction to test pattern, can reduce image fault; Adopt and hot spot and background segment are opened, the non-luminous region that those should not participate in evaluating can be removed; Adopt the mode of artificial setting and the automatic calculations incorporated of computing machine to obtain desirable gray threshold, utilize gray threshold accurately speck and background segment to be opened; Calculating dot matrix image is adopted to get rid of invalid hot spot; Adopt and the image in effective light spot, background and non-statistical region is shown with composograph with different colours respectively, to people's direct feel, utilize gray scale fluctuation allowable value to abate the noise impact; Manual intervention is chosen result to dot matrix setting, Iamge Segmentation and hot spot and is optimized and revised further; Above-mentioned technological means can make test result more objective, accurate; Adopt and calculate brightness uniformity, distributing homogeneity and sum of the two respectively to evaluate uniformity of luminance, then more comprehensive.Adopt brightness uniformity, distributing homogeneity and sum of the two evaluate uniformity of luminance, more comprehensively, therefore the present invention relative to existing method of testing more comprehensively, objective and accurate, and effectively, directly perceived, easy.
Accompanying drawing explanation
Fig. 1 is process flow diagram of the present invention;
Fig. 2 is the lattice luminous image of embodiment shooting;
Fig. 3 is the test pattern obtained after selected zone and deformity correction;
Fig. 4 is single array point schematic shapes
Fig. 5 is array image schematic diagram.
Embodiment
Below in conjunction with attached Example, the present invention is elaborated.
As shown in Fig. 1, the concrete steps of the present embodiment are:
With shooting 2 shooting point array light source 1 luminescence process, by the USB interface of computing machine 3, video is sent to computing machine 3, then from video the luminescent image of intercept point array light source 1, in described luminescent image, choose a rectangle region to be tested, as shown in Figure 2; Geometry deformity correction is carried out to the image in described rectangle region to be tested, generates test pattern, as shown in Fig. 3; Read the gray-scale value of each pixel in described test pattern; Setting gradation of image fluctuation allowable value Tc, if certain pixel is less than Tc with the gray scale difference of contiguous 8 pixels, then judging that grey scale change is caused by noise, is the gray-scale value of this pixel with the gray scale maximal value in contiguous 8 pixels; Artificial setting gradation of image threshold value Tr, is less than the pixel of Tr, judges that it does not belong to speck to gray-scale value, calculate overall gray threshold and the local threshold of test pattern further, speck 5 and background segment are opened with ostu image segmentation threshold algorithm; To there is the eight connectivity path that at least one grey scale change is less than Tc between the border of two specks if having, then two specks are merged into a speck, all pixels on communication path are also under the jurisdiction of this speck; According to true form and the feature of array point, the shape of array point in test pattern is set for oval, the numerical value that its characteristic parameter comprises semi-major axis and semi-minor axis is tentatively set, sketch the contours of single array dot image 4, finely tune array point patterns parameter again, characteristic parameter semi-major axis or the semi-minor axis numerical value of the principle search optimum of maximal value should be obtained by cross correlation value r, finally determine the shape of single array point
The computing formula of described r is:
Wherein, P is the set of all sub-pixel points of topography, and I is the set of all sub-pixel points corresponding with P coordinate position in test pattern, I
ijkbe the gray-scale value of the sub-pixel point of (i, j, k) for image coordinate in I, I
afor I
ijkmean value, P
ijkbe the gray-scale value of the sub-pixel point of (i, j, k) for image coordinate in P, P
afor P
ijkmean value;
A selected array point P in test pattern
00as the staring array point being positioned at the 0th row the 0th and arranging, if its coordinate is (x0, y0), calculate lattice parameter Lx1, Lx2, Ly1 and Ly2 according to the relative position of each array point and distance, as shown in Figure 5, then General Cell point P
mncoordinate be (x0+m*Lx1+n*Lx2, y0+m*Ly1+n*Ly2), wherein m and n is specific integer, represents that array point is positioned at m capable n-th and arranges (as shown in Figure 7); Centered by each array point coordinate, dilation operation is carried out by the shape of single array point in position, obtains array image; Test pattern is shown with composograph, wherein, the image in effective light spot, background and non-statistical region is respectively with red, blue, green three kinds of colors display, automatically processed by manual observation, judgement, selection or computing machine, result is chosen to dot matrix selection, Iamge Segmentation and hot spot and optimizes and revises further; Calculating the pixel quantity that single array dot image comprises is array point area Sp, add up each array dot image comprise the quantity of speck pixel as array point speck total area Se, if the ratio of Se and the Sp of certain array point is greater than 0.3, then judge that this array point is as effective light spot; Test pattern is divided into 9 regions equably, calculate gradation uniformity and the distributing homogeneity of effective light spot, evaluate uniformity of luminance with gradation uniformity, distributing homogeneity and gradation uniformity, distributing homogeneity sum, the computing formula of described brightness uniformity is:
Wherein, γ
1, γ
2..., γ
nthe average gray of each described effective light spot, γ
0the average gray of all described effective light spots, s
γbe grey scale deviation, γ is the numerical value weighing brightness uniformity;
The computing formula of described distributing homogeneity is:
Wherein, β
1, β
2..., β
nafter photo being divided into equably 9 regions, the hot spot number in each region, β
0the mean value of regional hot spot number, s
βit is hot spot number standard deviation; The image obtained in test process, data are preserved on a storage medium by artificial or self-timing, or exports display to and show, also can export other equipment to and be for further processing.
Claims (9)
1. an array light source uniformity of luminance method of testing, is characterized in that comprising the following steps:
The image of (a) acquisition point array light source luminescence process;
B () chooses region to be tested in described image;
C () generates test pattern;
D () reads the gray-scale value of each pixel in described test pattern;
E () setting gray threshold, opens speck and background segment;
F () calculates dot matrix distributed architecture, array point shape classification and characteristic parameter thereof, obtain array image;
G () calculates the pixel quantity that single array dot image comprises is array point area, calculate each array dot image comprise the speck total area of quantity as array point of speck pixel, if the ratio of the speck total area of certain array point and array point area is greater than setting value, then judge that this array point is as effective light spot;
H () calculates gradation uniformity and the distributing homogeneity of described effective light spot, evaluate uniformity of luminance with gradation uniformity, distributing homogeneity and gradation uniformity, distributing homogeneity sum, and the computing formula of described brightness uniformity is:
Wherein, γ
1, γ
2..., γ
nfirst, second ..., effective light spot described in n-th average gray, γ
0the average gray of all described effective light spots, s
γbe grey scale deviation, γ is the numerical value weighing brightness uniformity;
The computing formula of described distributing homogeneity is:
Wherein, β
1, β
2..., β
nafter test pattern being divided into equably n region, first, second ..., the n-th region hot spot number, β
0the mean value of regional hot spot number, s
βbe hot spot number standard deviation, γ is the numerical value weighing distributing homogeneity;
Calculate β and γ sum larger;
(i) preserve or export result of calculation.
2. method of testing according to claim 1, is characterized in that step f specifically comprises:
Shape classification and the characteristic parameter thereof of array point in test pattern are tentatively set according to the true form of array point and characteristic parameter, sketch the contours of the topography of single array point, finely tune array point patterns parameter again, the characteristic parameter of the principle search optimum of maximal value should be obtained by cross correlation value, finally determine the shape of single array point
The computing formula of described cross correlation value is
Wherein, r is cross correlation value, and P is the set of all sub-pixel points of topography, and I is the set of all sub-pixel points corresponding with P coordinate position in test pattern, I
ijkbe the gray-scale value of the sub-pixel point of (i, j, k) for image coordinate in I, I
afor I
ijkmean value, P
ijkbe the gray-scale value of the sub-pixel point of (i, j, k) for image coordinate in P, P
afor P
ijkmean value;
In test pattern, a selected array point is as staring array point, with staring array dot center coordinate for initial point, calculates lattice parameter, draw the coordinate of each array point according to the relative position of each array point and distance;
Centered by each array point coordinate, dilation operation is carried out by the shape of single array point in position, obtains array image.
3. method of testing according to claim 1 and 2, is characterized in that step e specifically comprises:
Setting gradation of image fluctuation allowable value;
If certain pixel is less than fluctuation allowable value with the gray scale difference of contiguous 8 pixels, the gray-scale value of this pixel is determined by the gray scale maximal value of being close in 8 pixels;
To there is the eight connectivity path that at least one grey scale change is less than fluctuation allowable value between the border of two described specks if having, then two specks are merged into a speck, all pixels on communication path are also under the jurisdiction of this speck.
4. method of testing according to claim 1 and 2, is characterized in that also being provided with following steps between step b and c:
Geometry deformity correction is carried out to the image in described region to be tested.
5. method of testing according to claim 3, is characterized in that also being provided with following steps between step b and c:
Geometry deformity correction is carried out to the image in described region to be tested.
6. method of testing according to claim 1 and 2, is characterized in that also being provided with following steps between step f and g:
The image in effective light spot, background and non-statistical region is shown with composograph with different colours respectively, dot matrix is selected, Iamge Segmentation and hot spot choose result and optimize and revise further.
7. method of testing according to claim 3, is characterized in that also being provided with following steps between step f and g:
The image in effective light spot, background and non-statistical region is shown with composograph with different colours respectively, dot matrix is selected, Iamge Segmentation and hot spot choose result and optimize and revise further.
8. method of testing according to claim 4, is characterized in that also being provided with following steps between step f and g:
The image in effective light spot, background and non-statistical region is shown with composograph with different colours respectively, dot matrix is selected, Iamge Segmentation and hot spot choose result and optimize and revise further.
9. method of testing according to claim 5, is characterized in that also being provided with following steps between step f and g:
The image in effective light spot, background and non-statistical region is shown with composograph with different colours respectively, dot matrix is selected, Iamge Segmentation and hot spot choose result and optimize and revise further.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410044024.7A CN104655403B (en) | 2014-01-29 | 2014-01-29 | Luminance uniformity test method of dot-matrix light source |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410044024.7A CN104655403B (en) | 2014-01-29 | 2014-01-29 | Luminance uniformity test method of dot-matrix light source |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104655403A true CN104655403A (en) | 2015-05-27 |
| CN104655403B CN104655403B (en) | 2017-04-19 |
Family
ID=53246793
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410044024.7A Expired - Fee Related CN104655403B (en) | 2014-01-29 | 2014-01-29 | Luminance uniformity test method of dot-matrix light source |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104655403B (en) |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105049734A (en) * | 2015-08-31 | 2015-11-11 | 广州市幸福网络技术有限公司 | License camera capable of giving shooting environment shooting prompt and shooting environment detection method |
| CN105243970A (en) * | 2015-11-19 | 2016-01-13 | 广东威创视讯科技股份有限公司 | Assessment method and device for LED uniformity |
| CN105447878A (en) * | 2015-12-14 | 2016-03-30 | 深圳市高斯贝尔家居智能电子有限公司 | Image quality test analysis method and system |
| CN105510006A (en) * | 2016-02-29 | 2016-04-20 | 四川聚能核技术工程有限公司 | Device and method for measuring evenness of LED area array light source |
| CN105869147A (en) * | 2016-03-23 | 2016-08-17 | 浙江东方光学眼镜有限公司 | Typoscope stray light recognition method |
| CN105898292A (en) * | 2016-01-06 | 2016-08-24 | 中山大学 | 3D display subjective luminance uniformity quantitative measurement method and device |
| CN109186941A (en) * | 2018-08-09 | 2019-01-11 | 信利光电股份有限公司 | A kind of detection method and system of light source uniformity |
| CN109544552A (en) * | 2018-12-06 | 2019-03-29 | 合刃科技（深圳）有限公司 | A kind of grating lossless detection method and system |
| CN109767425A (en) * | 2018-12-13 | 2019-05-17 | 合刃科技（武汉）有限公司 | Machine vision light source uniformity assesses device and method |
| CN109959498A (en) * | 2019-03-29 | 2019-07-02 | 珠海达明科技有限公司 | A kind of array light-emitting component quality detecting system and its application method |
| CN111294521A (en) * | 2018-12-06 | 2020-06-16 | 北京京东尚科信息技术有限公司 | Light supplementing method and device and computer readable storage medium |
| CN111609998A (en) * | 2020-05-11 | 2020-09-01 | 歌尔股份有限公司 | Detection method and detection device for illumination uniformity and readable storage medium |
| CN111767623A (en) * | 2019-03-14 | 2020-10-13 | 华东交通大学 | Novel method for evaluating full-range illumination uniformity based on human vision |
| CN112155511A (en) * | 2020-09-30 | 2021-01-01 | 广东唯仁医疗科技有限公司 | Method for compensating human eye shake in OCT (optical coherence tomography) acquisition process based on deep learning |
| CN112747906A (en) * | 2021-01-28 | 2021-05-04 | 歌尔光学科技有限公司 | Light source detection method, detection device and readable storage medium |
| CN113075135A (en) * | 2021-03-31 | 2021-07-06 | 中国科学院长春光学精密机械与物理研究所 | Method for correcting accurate position of light spot array of snapshot type imaging spectrometer |
| CN113281310A (en) * | 2021-04-06 | 2021-08-20 | 安徽工程大学 | Method for detecting light transmittance and uniformity of optical medium material |
| CN113820576A (en) * | 2020-06-17 | 2021-12-21 | Tcl科技集团股份有限公司 | Method and device for testing light-emitting diode device |
| CN116067627A (en) * | 2023-02-20 | 2023-05-05 | 浙江禾川科技股份有限公司 | Point light source light quantity distribution equalization correction system and correction method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09318448A (en) * | 1996-05-27 | 1997-12-12 | Nissan Motor Co Ltd | Judgment apparatus for irregular color of metallic finish and evaluation method |
| JP2001266122A (en) * | 2000-03-17 | 2001-09-28 | Dainippon Printing Co Ltd | Method and device for inspecting irregular color defect |
| CN1791231A (en) * | 2004-12-17 | 2006-06-21 | 上海永新彩色显像管股份有限公司 | Chromatic display unit white field homogeneity testing method and system |
| CN102508144A (en) * | 2011-10-26 | 2012-06-20 | 西安电子科技大学 | Method for measuring dark signal non-uniformity and photon response non-uniformity of photons of CCD (charge coupled device) chip |
| CN103354617A (en) * | 2013-07-03 | 2013-10-16 | 宁波大学 | Boundary strength compressing image quality objective evaluation method based on DCT domain |
| CN103440634A (en) * | 2013-09-11 | 2013-12-11 | 中国科学院电子学研究所 | Method for adaptively adjusting infrared remote sensing image contrast |
-
2014
- 2014-01-29 CN CN201410044024.7A patent/CN104655403B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH09318448A (en) * | 1996-05-27 | 1997-12-12 | Nissan Motor Co Ltd | Judgment apparatus for irregular color of metallic finish and evaluation method |
| JP2001266122A (en) * | 2000-03-17 | 2001-09-28 | Dainippon Printing Co Ltd | Method and device for inspecting irregular color defect |
| CN1791231A (en) * | 2004-12-17 | 2006-06-21 | 上海永新彩色显像管股份有限公司 | Chromatic display unit white field homogeneity testing method and system |
| CN102508144A (en) * | 2011-10-26 | 2012-06-20 | 西安电子科技大学 | Method for measuring dark signal non-uniformity and photon response non-uniformity of photons of CCD (charge coupled device) chip |
| CN103354617A (en) * | 2013-07-03 | 2013-10-16 | 宁波大学 | Boundary strength compressing image quality objective evaluation method based on DCT domain |
| CN103440634A (en) * | 2013-09-11 | 2013-12-11 | 中国科学院电子学研究所 | Method for adaptively adjusting infrared remote sensing image contrast |
Non-Patent Citations (1)
| Title |
|---|
| 全先荣: "点阵式辐射定标光源的研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105049734A (en) * | 2015-08-31 | 2015-11-11 | 广州市幸福网络技术有限公司 | License camera capable of giving shooting environment shooting prompt and shooting environment detection method |
| CN105049734B (en) * | 2015-08-31 | 2018-08-24 | 广州市幸福网络技术有限公司 | It can carry out the license camera and shooting environmental detection method of shooting environmental shooting prompt |
| CN105243970A (en) * | 2015-11-19 | 2016-01-13 | 广东威创视讯科技股份有限公司 | Assessment method and device for LED uniformity |
| CN105447878A (en) * | 2015-12-14 | 2016-03-30 | 深圳市高斯贝尔家居智能电子有限公司 | Image quality test analysis method and system |
| CN105898292A (en) * | 2016-01-06 | 2016-08-24 | 中山大学 | 3D display subjective luminance uniformity quantitative measurement method and device |
| CN105510006A (en) * | 2016-02-29 | 2016-04-20 | 四川聚能核技术工程有限公司 | Device and method for measuring evenness of LED area array light source |
| CN105869147A (en) * | 2016-03-23 | 2016-08-17 | 浙江东方光学眼镜有限公司 | Typoscope stray light recognition method |
| CN105869147B (en) * | 2016-03-23 | 2018-11-09 | 浙江东方光学眼镜有限公司 | A kind of amblyopia visual aid stray light recognition methods |
| CN109186941A (en) * | 2018-08-09 | 2019-01-11 | 信利光电股份有限公司 | A kind of detection method and system of light source uniformity |
| CN111294521A (en) * | 2018-12-06 | 2020-06-16 | 北京京东尚科信息技术有限公司 | Light supplementing method and device and computer readable storage medium |
| CN109544552A (en) * | 2018-12-06 | 2019-03-29 | 合刃科技（深圳）有限公司 | A kind of grating lossless detection method and system |
| CN111294521B (en) * | 2018-12-06 | 2023-04-07 | 北京京东尚科信息技术有限公司 | Light supplementing method and device and computer readable storage medium |
| CN109767425A (en) * | 2018-12-13 | 2019-05-17 | 合刃科技（武汉）有限公司 | Machine vision light source uniformity assesses device and method |
| CN109767425B (en) * | 2018-12-13 | 2021-09-14 | 合刃科技（武汉）有限公司 | Machine vision light source uniformity evaluation device and method |
| CN111767623A (en) * | 2019-03-14 | 2020-10-13 | 华东交通大学 | Novel method for evaluating full-range illumination uniformity based on human vision |
| CN111767623B (en) * | 2019-03-14 | 2022-04-29 | 华东交通大学 | Novel method for evaluating full-range illumination uniformity based on human vision |
| CN109959498A (en) * | 2019-03-29 | 2019-07-02 | 珠海达明科技有限公司 | A kind of array light-emitting component quality detecting system and its application method |
| CN111609998A (en) * | 2020-05-11 | 2020-09-01 | 歌尔股份有限公司 | Detection method and detection device for illumination uniformity and readable storage medium |
| CN113820576B (en) * | 2020-06-17 | 2023-11-14 | Tcl科技集团股份有限公司 | Method and device for testing light-emitting diode device |
| CN113820576A (en) * | 2020-06-17 | 2021-12-21 | Tcl科技集团股份有限公司 | Method and device for testing light-emitting diode device |
| CN112155511A (en) * | 2020-09-30 | 2021-01-01 | 广东唯仁医疗科技有限公司 | Method for compensating human eye shake in OCT (optical coherence tomography) acquisition process based on deep learning |
| CN112747906A (en) * | 2021-01-28 | 2021-05-04 | 歌尔光学科技有限公司 | Light source detection method, detection device and readable storage medium |
| CN113075135B (en) * | 2021-03-31 | 2022-07-15 | 中国科学院长春光学精密机械与物理研究所 | Method for correcting accurate position of light spot array of snapshot type imaging spectrometer |
| CN113075135A (en) * | 2021-03-31 | 2021-07-06 | 中国科学院长春光学精密机械与物理研究所 | Method for correcting accurate position of light spot array of snapshot type imaging spectrometer |
| CN113281310A (en) * | 2021-04-06 | 2021-08-20 | 安徽工程大学 | Method for detecting light transmittance and uniformity of optical medium material |
| CN116067627A (en) * | 2023-02-20 | 2023-05-05 | 浙江禾川科技股份有限公司 | Point light source light quantity distribution equalization correction system and correction method |
| CN116067627B (en) * | 2023-02-20 | 2023-08-29 | 浙江禾川科技股份有限公司 | Point light source light quantity distribution equalization correction system and correction method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104655403B (en) | 2017-04-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104655403A (en) | Luminance uniformity test method of dot-matrix light source | |
| CN108492776B (en) | Intelligent external optical compensation method for AMOLED screen brightness unevenness | |
| CN104821157B (en) | Show correction system | |
| CN105247607A (en) | Methods and systems for measuring and correcting electronic visual displays | |
| CN105185314A (en) | Uniformity compensation method for LED display screen | |
| CN110853105B (en) | Method and device for simultaneously positioning RGB (red, green and blue) sub-pixels and application | |
| CN107180605A (en) | A kind of method for eliminating display device Mura, elimination display device Mura devices and display device | |
| CN109637434A (en) | Bearing calibration, correction system and the machine readable storage medium of mosaic display screen | |
| CN114495803A (en) | Mura repairing method of display panel | |
| CN114299070B (en) | Method and related device for detecting mura defects of display screen | |
| CN109191386B (en) | BPNN-based rapid Gamma correction method and device | |
| CN106937109B (en) | The method that low cost judges resolution ratio of camera head level | |
| CN109978864A (en) | Display panel detection system, method, apparatus and storage medium | |
| CN104658461B (en) | The method of testing of display lighting uniformity | |
| CN110310596A (en) | A kind of the GAMMA adjusting initial value prediction technique and system of OLED mould group | |
| CN111599294B (en) | Method and device for evaluating granular sensation of display screen | |
| CN106846328B (en) | A kind of video image stabilization judgement and the tunnel brightness detection method based on video | |
| CN110160750B (en) | LED display screen visual detection system, detection method and detection device | |
| CN116862810A (en) | Brightness adjusting method and device | |
| CN115526883A (en) | LED lamp bead detection method and device, computer equipment and storage medium | |
| CN105280124A (en) | Gamma measurement method and device for four-color display system | |
| CN115602093A (en) | Method, system and equipment for performing Demura compensation based on white picture | |
| US20150325175A1 (en) | Image Display Device, Method For Controlling Image Display Device, Control Program, And Recording Medium | |
| JP2019091308A (en) | Object detector, image analysis device, object analytical method, image analysis method, program, and learning data | |
| US7330580B2 (en) | System and method for inspecting an LCD panel |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170419 Termination date: 20190129 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |