The Development of Luminance Uniformity Measurement for CNT-BLU Based on Human Visual Perception Kuo-Hao Tang, Yueh-Hua Lee, Feng Chia University Abstract-- CNT-BLU (Carbon NanoTube backlight unit), an emerging backlight component for LCD, has several advantages such as light weight, superior color performance etc, and therefore have the potential to replace traditional CCFL (Cold Cathode Fluorescent Lamps) backlight unit. However, the current uniformity of CNT-BLU still can not compete with that of CCFL due to immature manufacturing process. The CNT-BLUs under current technology limits produce dotted appearance, and thus prevent it from using existing luminance uniformity measurements such as VESA or ISO Standard, which is more suitable for measuring CCFL-LCD with relatively good uniformity. This study developed a new method, Line Uniformity, to monitor the uniformity improvement for CNT-BLU before it can be accepted by the market. This method was compared with VESA and U Formula with respect to human perception. A set of CNT-BLU images with different levels of dotted appearances was presented to 5 participants. The subjective acceptance threshold for images with the same level of dotted appearances was then calculated. The uniformities for VESA, U Formula, and Line Uniformity were calculated and fitted to the subjective acceptance threshold separately. The results showed that Line Uniformity was better fitted to acceptance threshold with R 2 ranging from. to.92 whereas VESA and U Formula generated R 2 ranging only from. to.49. Keywords-- CNT-BLU, human perception, luminance uniformity, threshold. I. INTRODUCTION As the display size increases, the cost associated with LCD backlight units (BLU) becomes larger. When compared with CCFL backlight units, CNT (Carbon Nanotube) backlight units have the advantages of less power consumption, superior color performance, and no toxic chemicals [8]. Under the RoHS (Restriction of Hazardous Substances) regulations, CCFL-BLU was restricted from July th due to the toxic mercury (Hg) gas. In addition, without the optical film and diffuser that used in CCFL-BLU, CNT-BLU can save up to % of the BLU cost. Hence, CNT-BLU has been considered as a potential candidate that may replace CCFL-BLU for the next generation of large screen LCD. Carbon Nanotube (CNT) was discovered by Iijima in 99 and since then many studies focus on the properties of CNT, particularly the field emission effect and its applications on lighting, back light unit for LCD, or field emission display (FED) [5],[7]. The light emission principle of CNT-BLU are similar to that of CRT (Cathode Ray Tube) display, both based on tunneling of electrons through the surface potential barrier. In stead of using a single emitting source like CRT, CNT-BLU uses an array of emitters, and each emitter is corresponding to each pixel. Thus, the distance between cathode and anode can be effectively shortened, which makes the flat products possible. In terms of manufacturing process, mass production of CNT-BLU is still under development and some issues are yet to be addressed, such as of luminance uniformity, light up control, material and manufacturing costs etc. Luminance uniformity is a very important criterion for CNT-BLU. It relates to the end users perception and it also affects the grading and pricing strategy of the product. However, a variety of physical factors in the manufacturing process such as non-uniformly distributed CNT material and foreign particles within the CNT material may cause luminance uniformity related problems. When compared with mainstream flat panel display products such as LCDs, CNT-BLU shows different appearance due to such manufacturing flaws. Mura in LCD is broadly discussed and has three different pattern types, spot Mura, line Mura and region Mura [3]. There are two categories of luminance uniformity phenomenon for CNT-BLU, the first one is mottled background defect, and the second one is pattern defect. From Fig., the mottled background defect is a randomly dotted background with different shadings of spots, representing a typical BLU image under current manufacturing processes. On the other hand, pattern defect are very similar to LCD Mura, which also include line and region in shape emerged from mottled background as shown in Fig. 2. In order to measure luminance uniformity, four widely used luminance uniformity measurements are presented below ()-(4). These methods are based on sampling multiple points and only consider the maximal and minimal luminance among sampled points. VESA: Non-Uniformity= [-(L min/l max )]*% () ISO: Uniformity=(L max /L min ) (2) Mura is a Japanese word and has been adopted in English. It means the imperfections of a LCD pixel matrix surface that are visible when the screen is driven to a constant gray level. It may have different shapes: Line, spot and region etc.
SPWG: Uniformity = [(L max -L min ) / L max ] *% (3) TCO: Luminance Variation = (L max /L min ). (4) Where L max and L min represent the maximal and minimal luminance value among measured points. region defect line defect Fig.. CNT-BLU with pattern defect: line, region defects with a parti-colored background Fig. 2. CNT-BLU without patterned defect, and has a parti-colored background Fig. 3. 23 CCFL BLU W W 2 W H H 2 H Fig. 4. Six measured lines in Line Uniformity method Among these standards, VESA standard is widely recognized because it provides a comprehensive catalog of versatile optical measurements and informative technical discussions well-grounded in solid metrology [2]. A total of 9 or points are required to be measured according to the size of the panel when using VESA standard. Such sampling measurement of luminance is quite risky for CNT-BLU, which has obvious mottled appearance. The use of these measuring methods, considering only the minimal and maximal luminance, may not reflect the true luminance uniformity. In order to calculate the luminance uniformity more precisely, Reference [] suggested that luminance uniformity measurement could be based on line measurement, which is, measuring luminance pixel by pixel on a line across the panel. They also proposed that the ratio of minimal and maximal luminance of measuring points should not be under.7 to accept a panel. The idea of cross section measurement was mentioned in another research. Reference [] provided equation (5) that the average and standard deviation of luminance of measured lines were used to represent the LED-BLU uniformity. σ = L U % (5) L ave Where σ L and L ave stands for standard deviation and average of measuring luminance respectively. From Fig. 3, it can be seen that a CCFL-BLU has a much better luminance uniformity compared with CNT-BLU shown in Fig. 2. The difference may explain why VESA being suitable for CCFL-BLU, may not be a good measure for CNT-BLU, especially during its research and development stage. The purpose of this study is to develop a more appropriate method to depict the luminance uniformity for CNT-BLU with mottled background defect (for pattern defect, please see reference [] ) and compare it with VESA Standard and U Formula, in order to evaluate the consistency with human perception. II. Development of Line Uniformity In order to present the luminance uniformity of the mottled background of a CNT-BLU, Line Uniformity was proposed. Six lines are to be measured for Line Uniformity. This idea comes from the 9 points measurement for LCD according to VESA standard. The locations of these 9 points are as shown in Fig. 4. The 3 points on the left side are located at / of the BLU width from the left edge. The 3 top points are located at / of the BLU height from the top edge. The 3 points on the right side and 3 bottom points are symmetric with respect to the central vertical and horizontal lines. Six lines are connected through these 9 points as shown in Fig. 4. The luminance of each pixel on all the line are measured and the sum of the absolute values of the difference between the two
adjacent pixels across all six lines is calculated to show the Line Uniformity as shown in (). The larger the Line uniformity, the worse the luminance uniformity of the panel is. With this equation, the luminance variance between two adjacent pixels can be detected. Line Uniformity = n j i= j= L ( i, j+ ) i= n i L ( i, j) () Where L (i,j) stands for the change of luminance value of j th pixel on i th line, and n i stands for the number of pixel on i th line. III. Development of CNT-BLU Image Model The BLU is a module providing light source for an LCD panel, which allows less than % of light from BLU passing through. Therefore, the meaningful way to measure the luminance uniformity for a CNT-BLU is after it being assembled with an LCD panel. Due to that the CNT-BLU manufacturing is still in pilot run stage, the numbers of available BLU were small, and even less being assembled with an LCD panel. To cope with this limitation, a CNT-BLU image model was developed for this study to present simulated CNT-BLU images on a regular LCD with relatively high fidelity. A. Transformation from CNT-BLU to LCD with CNT-BLU The construction of transformation equation between the luminance of CNT-BLU and that of assembled with LCD panel was conducted in a major research institute in Taiwan. The measuring environment was controlled at luminance less than lux, temperature at 25 Celsius degree, humidity at 35%, and gate voltage of CNT-BLU controlled to a fixed level at 34 volts. Since the luminance of CNT-BLU changes according to the anode current, in order to cover a more complete luminance range, anode current was adjusted from 2mA to 22mA with ma per step, the corresponding measured luminance of CNT-BLU increased from 22.4 nits to 223.5 nits. There were 5*49 points measured in a panel and 2 steps in terms of current control generating,88,5 (2*5*49) luminance measurements for building the transformation equation between the luminance of CNT-BLU and that of CNT-BLU with LCD panel. Regression modal was used to fit the measured data and the fitted model (R 2 =.98) was shown in Fig. 5 (left). B. Transformation from LCD with CNT-BLU to a regular LCD To reproduce the image from an LCD with CNT-BLU onto a regular LCD display, Acer AL97, a 9 inches LCD was first chosen as an experimental apparatus. Given a fixed brightness and contrast setting for this LCD, the function between the luminance measured from this LCD and the gray level of the panel, i.e., from RGB(,, ) to RGB(255, 255, 255), can be determined (R 2 =.99) as shown in Fig. 5 (right). Eighteen original CNT-BLUs were used in this study. These images of CNT-BLUs were taken by using ProMetric system where the luminance of each CNT-BLU pixel can be recorded. Then with these two functions, these images of CNT-BLU can be converted to predicted luminance as if an LCD panel was assembled, then finally transformed to a RGB value representing the corresponding luminance. As we mentioned before, the current quality of CNT-BLU is not up to the market, and the images of the CNT-BLUs were far below users acceptance threshold. To simulate the future improvement of the image quality and still keep the characteristics of CNT-BLU, the Gaussian Blur function [9] was used to mimic this improvement process. For each of the 8 images, blurring levels were generated. Level was the original image and the Level had a uniformity similar to a normal LCD. C. Subjects and Experimental Task Fifteen engineering school students aged from 23 to 2 participated in this experiment. Before the experiment, the LCD used in the experiment needed to warm up at least 3 minutes to obtain a stable color response. Each participant had to judge all the 8 images at levels with 3 brightness levels, which comprised of 594 images. They were asked to answer a yes-no question with regard to do you think this LCD panel will be accepted by customers? and the acceptance threshold values calculated from these answers were treated as dependent variable. The sequence of viewing images was randomized for all participants.
Fig. 5. The transformation model of CNT-BLU to CNT-BLU with LCD screen and transformation model of luminance of LCD to its gray level between less than. to.487 as suggested by Fig. 7 Finally, IV. RESULTS it can be seen that Line Uniformity generated the best results The acceptance thresholds of all the 594 images used in this from. to.927 (Fig. 8), which means, luminance study were calculated from the responses of all the participants. uniformity that measured using Line Uniformity made a better Their luminance uniformities of each image for the three prediction to human perception. On the contrary, the use of methods, namely, VESA Standard, U Formula and Line VESA Standard and U Formula could not provide such Uniformity were also calculated. Fig. shows the scatter consistency between human perception and the measured diagrams between VESA Standard and acceptance threshold uniformity. R square values in these two cases were under.4. under three brightness conditions. Sigmoidal modal, which was However, VESA Standard, that uses only maximal and widely used to describe the threshold of human perception, was minimal luminance of measured points had higher R square used to fit the diagram. The R square values of each modal were value than those of U Formula, which requires information with from.225 to.392 as shown on Fig. Same regression model regard to all points on the measured line. Hence, the use of applied to U Formula showed that the R square values were VESA Standard had better efficacy than the use of U Formula. Low Brightness R 2 =.392 Medium Brightness R 2 =.275 High Brightness R 2 =.225 4 4 4 3 4 5 7 VESA (Non-Uniformity %) 3 4 5 7 VESA (Non-Uniformity %) 3 4 5 7 VESA (Non-Uniformity %) Fig.. The acceptance threshold figure under three brightness condition: VESA Standard Low Brightness R2=.529E-2 Medium Brightness R 2 =.487 High Brightness R 2 =2E-5 4 4 4.85.9.95..5. U Formula (Uniformity)..5.7.75..85.9.95..5 U Formula (Uniformity).55..5.7.75..85.9.95. U Formula (Uniformity) Fig. 7. The acceptance threshold figure under three brightness control: U Formula Low Brightness R2=. Medium Brightness R2=.89 High Brightness R 2 =.927 4 4 4 E-3.. Line-Uniformity (Non-Uniformity) log (/pixel/pixel) E-3.. Line-Uniformity (Non-Uniformity) log (/pixel/pixel) E-3.. Line-Uniformity (Non-Uniformity) log (/pixel/pixel) Fig. 8. The acceptance threshold figure under three brightness condition: Line Uniformity
Even the Line Uniformity fitted better against acceptance threshold, the brightness affected the fitting as shown in Fig. 9. Given the same calculated Line Uniformity, high brightness generated a better acceptance threshold than lower brightness. To obtain a better predictive model, equation was modified and the luminance used to calculate Line Uniformity was standardized with brightness. The result was shown in Fig.. The three threshold functions for different brightness conditions overlapped each other and the undesired brightness effect almost disappeared. The R square value for this combined function was about.88, which means the luminance uniformity measurement still maintained a good consistency with human perception across different brightness levels. V. CONCLUSION The focus of this study was to find a more effective way to measure the uniformity quality of the under-developing CNT-BLB since many current uniformity standards are not suitable for this purpose. Line Uniformity was proposed and compared with another two widely accepted uniformity measures, namely, VESA Standard and U Formula. The results showed that Line Uniformity outperformed VESA Standard and U Formula based on human perceived judgment using a set of simulated CNT-BLU images. Although some may argue that VESA Standard and U Formula are more efficient than Line Uniformity, the calculation for Line Uniformity is rather simple and not seems to be a problem, especially when the production rate is relatively low during the CNT-BLU development stage. The U Formula, which also relies on the information of a whole line, even performed worse than VESA Standard. Even given the same amount of information like given to Line Uniformity, the calculation from six lines using U Formula only generated an R square value of.329, far below the Line Uniformity case. As we mentioned above, CNT-BLU has the typical defect of mottled appearance, the statistics that use in U Formula may be too rough for describing such detailed variation between adjacent pixels. The results suggest that Line Uniformity may be a more appropriate indicator than VESA Standard and U Formula for evaluating the luminance uniformity for CNT-BLU during its developing stage. Since CNT-FED has the same light emission principle with CNT-BLU, we expect that this Line Uniformity can also be applied to CNT-FED, which may need a longer developing time due to its complexity. The different light emission principle of CNT-FED and its mottled background compared with LCD might also suggest that a line-based luminance uniformity measure may be more appropriate than a point-based uniformity measure, not only for its developing stage, but also for commercialized CNT-FED in the market. Fig. 9. The acceptance threshold under three brightness conditions: Line Uniformity 4 Line Uniformity (Non- Uniformity) E-4 E-3. Line Uniformity (Non-Uniformity) R 2 =.88 Fig.. The standardized of three brightness conditions VI. ACKNOWLEDGEMENT This research was partially supported by the National Science Council of Taiwan, R.O.C. (NSC 9-222-E-35-23.) VII. REFEREENCE [] Chu, M., Coleman, Z., Henrickson, K., and Yeo, T. (). Novel high brightness LED backlight design and optimization. ADEAC Conference. [2] Downen, P. (). A closer look at Flat-Panel-Display measurement standards and trends. SID. [3] Lee J. Y. and Yoo S. I. (4). Automatic Detection of Region-Mura Defect in TFT-LCD. IEICE TRANS. INF. & SYST. E87-D, 237-2378. [4] Li, Y., Zhu, C., and Liu, X. (2). Field Emission Display with Carbon Nanotubes Cathode: Prepared by a Screen-Printing Process. Diamond and Related Materials,, 845-847. [5] Lin, W.C., Yang, Y.J., Hsieh, G.W., Tsai, C.H., Chen, C.C., and Liang, C.C. (). Selective local synthesis of nanowires on a microreactor chip. Sensors And Actuators A: Physical, SNA 5283, 8. (to be published)
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