The method to unidirectionally align semiconductor quantum rods (QRs) by the photo-induced alignment technique is disclosed, which has originally been developed for the alignment of liquid crystals. It is shown that the strategy facilitates the alignment of highly luminescent CdSe/CdS core/shell QRs in the aligned liquid crystal monomer (LCM), obtaining solid QRs in liquid crystal polymer (LCP) matrix after UV polymerization. Optical and characterization reveals QRs alignment with highly polarized emission, indicating the high order parameter. In application aspects, the microscale (down to 2 μm domain size) pattern alignments of QRs in LCP matrix show potential in photonic and security areas; the combination of QR/LCP composite film with liquid crystal technology present the new photo-emissive displays; the QR enhancement film improves both color performance (>100% NTSC) and optical efficiency (> 8%) for modern liquid crystal display applications.

In order to analyze the effect of different thickness of C60 on optical and electrical properties of top-emitting OLED, in experiment, the transmittance of ETL/EIL/Mg∶Ag/matching layers were numerically calculated and two top OLED with common cathode configurations were fabricated. The optical and electrical properties of OLED devices prepared with different thickness of C60 refractive index matching layers were analyzed. The results showed, the complex films with different C60 thickness have different transmittance, the complex films have high transmittance in wide range of wavelengths when C60 film thickness is 30~40 nm, the CIEx and CIEy values of transmittance spectra are extremely near to the equal energy (0.33,0.33). In addition, it can be found that the electroluminescence spectra and the chromaticity coordinates of OLED devices are also heavily related to the thickness of C60 refractive index matching layers, which is consistent with the numerical results of transmission spectrum of multilayer (ETL/EIL/Mg∶Ag/C60) at different thickness of C60 thin films and indicate that the luminous brightness and the color coordinates of top-emitting white light devices can be adjusted by different thickness of C60 refractive index matching layer to achieve white light emission close to equal energy.

The mainstream TFT-LCD devices have the problem of high power consumption. On account of canceling the use of polarizer and color filter, the MEMS based display is more suitable for low power applications. For mass manufacturing of MEMS displays, it is significant to match TFT-LCD with MEMS based display, including material and process. This paper systematically introduces the MEMS and TFT-LCD process, analyzes three main display modes based on MEMS. Some work and research progress of applying low cost TFT LCD technology to these MEMS based display technologies are described in detail. The development trend of MEMS based display technology is also discussed.

Liquid crystal drop process is the key to the TFT -LCD technology. Generally, the selection of liquid crystal drop amount of products refer to the range of liquid crystal without cold bubble and gravity Mura, that is, LC Margin. The narrower the margin is, the smaller the range of upper and lower limits of the liquid crystal center distance of the product, and the cold bubble and gravity Mura are liable to occur during the process fluctuation. In this paper, a method of liquid crystal drop by panel is proposed according to the PS height of color filter for products with narrow LC Margin (≤3%). There is no cold bubble and gravity Mura in the test of high and low temperature during the production process with this method, at the same time, the liquid crystal dropping process was optimized. It provides a new solution for products with narrow LC Margin.

To improve the quality of RGBW liquid crystal display module, based on tested data of RGBW liquid crystal display module and theory analysis, the method to improve RGBW module is proposed. Trough FPGA signal conversion algorithm, we can get the RGBW automotive LCD module with 50% transmittance increased. As the color filter (CF) is changed, the RGBW LCD has some issues, such as crosstalk, color cast and horizontal stripes flashing. By testing different polarity reversal drive corresponding waveform and CF permutation combination, the reasons of the problem is concluded. Results show that the RGBW LCD pixels in the polar line up with the need of the CF match, otherwise will occur crosstalk, color cast and horizontal stripes flashing. Counterparts in the design of LCD module, the polarity of the same color and same line pixels need positive and negative balance, otherwise the display quality of the module will be degraded.

In order to solve the problem of complex driving and high requirement of processor in TFT LCD, a display system is designed to drive the TFT LCD with MUC interface through serial port control. The hardware of the system is composed of STM32F4 processor and TFT LCD. Stm32f4 is used to drive TFT LCD and provide control channel to the external processor using TFT LCD display system through its serial port. The software uses μC/OS-Ⅲ operating system to write the bottom driver and driver control interface program, and uses DMA to read the serial port data. The hardware interface of the system is simple, only two I/O lines are needed to control the TFT LCD. The system can support four external processors to control the TFT LCD through the serial port. The serial port transmission rate is 2.4 kB/s~2 MB/s. The experimental results show that the system is stable and reliable, the display effect is clear and smooth, the drive and use of TFT LCD are simplified, and the adaptability and use range of TFT LCD are expanded.

During the process of updating the FPGA program and display parameters of the LED display control system, unexpected situations such as power failure or incorrect erasure may be encountered, which can result in the system to fail to work. In order to improve the reliability of the system, the FPGA program backup and system self- recovery are studied in this paper. Firstly, the MultiBoot configuration principle of Xilinx Spartan-6 FPGA is introduced. Then, according to the requirements of FPGA program and display parameter setting, the flash memory multi-region program and display parameter backup storage method are studied through the hardware design. Through the detailed programming of the FPGA MultiBoot configuration module, automatic call backup, automatic judgment, and hot restart of the program are realized. Finally, the generation method of the FPGA main and backup program firmware files is introduced. By simulating the FPGA program update error, it is verified that the system could call the ICAP setting register to trigger the IPROG command, and make sure the FPGA hot start to call the backup program to reconfigure. As a result, the stability and reliability of the LED control system updating and display parameter setting process are met by the practical application of FPGA MultiBoot configuration.

Aiming at the problems of poor hand-time tracking, low recognition accuracy and environmental impact, a hand tracking method based on neural network and Kalman filtering is proposed. The method firstly locates the detection target appearing in the video through the neural network, then estimates the target motion by Kalman filter, compares the estimated result with the detected target in the next frame image, and finally detects the target, tracking and displaying the trajectory of the hand movement in real time. Experiments show that the method can track multiple hand targets in real time and keep tracking when the cross and deformation occur during hand movement. The average processing frame number is 21.212 f/s, and the tracking accuracy rate is 94.88%. It basically meets the requirements of stable, reliable, high real-time and high robustness of hand tracking.

Aiming at the high-precision classification problem of digital images, a new digital image classification algorithm is proposed. In this algorithm, the local binary patterns (LBP) operator is used to construct the LBP image of the digital image, and then the histogram of the LBP graph is used to construct the feature vector of the image sample. Finally, the training data set constructed by the eigenvectors of a large number of samples is sent to the least squares support vector machines (LSSVM) for the construction of the classification model. In the classification test of test data sets, the proposed algorithm is compared with traditional support vector machine algorithm, extreme learning machine algorithm and Hopfield neural network method. The LBP-LSSVM algorithm presented shows excellent performance in the testing of typical performance indicators such as macro-precision rate, macro-recall rate and classification time.

The color reproduction capability of the color digital devices directly affects the final rendering effect of color images, and is an important indicator of the performance design of the color digital devices. In order to study the color reproduction ability of different color digital devices under low light, a simple and fast visual objective color reproduction ability evaluation method is proposed. This method firstly converts the RGB three-primary color space to CIELAB color space, and establishes a comprehensive and objective quantitative evaluation index in the CIELAB color space based on CIEDE2000 color difference formula. Finally, a host computer software program is developed based on the VC++ software platform, which can realize the on-site evaluation of the color reproduction ability of color digital equipment. The experimental results show that the evaluation method is in good agreement with the subjective visual perception, and can provide an effective evaluation method for the color reproduction ability of color digital devices in a low light environment.

In order to improve the recognition accuracy and implementation performance of road traffic signs, an improved LeNet-5 convolutional neural network structure is proposed to train 18 kinds of traffic sign images. Firstly, in the detection phase, the light-weight segmentation algorithm based on color and Hough transform algorithm is used to extract the target area of traffic signs, and the complexity of the control algorithm makes the recognition system basically meet the real-time requirements, and then LeNet-5 is used to classify and recognize traffic signs. The results show that the traffic signs are successfully identified by driving in the algorithm of this paper, and the running speed reaches 16.9 Hz, which basically meets the performance requirements of traffic sign recognition, such as stability, real-time and so on.

The cooperative representation algorithm has the characteristics of rapid classification of face images, but in the case of single or undersample, the complex change of face recognition rate is not ideal enough to meet the engineering requirements. For this problem, a cooperative representation of face recognition algorithm with a mixed internal variable-base sparse dictionary is proposed. Firstly, with the help of the change process of different faces collected in the same environment, the common features of the change of the face are extracted and the invariant basis is generated, the generality of the invariant basis generated by the common features of two or more different changes of the face is improved, and the sparse dictionary of the change between the training sample and the test sample is established. With the help of the dictionary, the training samples can construct the feature faces of the test samples approximately, so as to expand the training sample set, the characteristic face of the test sample is constructed. Using the AR, ORL, Yale and Yale B library for identification experiments, the results show that this algorithm can effectively improve the recognition rate of the cooperative representation algorithm, and increase the recognition rate by 7.33% to 33.17% in the case of undersamples, and 6.78% to 24.47% in the case of single samples.

Fuzzy c-means algorithm based on gray-level is a fast image segmentation algorithm, which cannot effectively segment the object pixels and background pixels of the non-destructive testing (NDT) image with the characteristics of unbalanced gray distribution. Then an improved fuzzy C-means algorithm based on gray-level (IFCMG) is proposed. Firstly, the expression of total membership degree of each cluster is constructed by using pixel numbers and membership degrees of gray-level, and it is integrated into the objective function, which can equalize the contribution of the object pixels and background pixels to the objective function. Secondly, the new membership degree and cluster center are strictly deduced. And then, considering that the density of clusters also affects the clustering results, we design the formula of compactness and integrate it into the clustering process. Finally, the NDT images are used for segmentation experiment. For each image, IFCMG has higher index values of F~~value when the images are disturbed by different noise levels. We comprehensively evaluate the values of F~~value obtained above, and find that the comprehensively evaluation value of the proposed algorithm is 26.13%, 16.46%, 13.75% and 25.10% higher than those of the comparison algorithms, respectively. The proposed algorithm can effectively segment NDT images with unbalanced gray distribution, which expands the application scope of fuzzy C-means algorithm based on gray-level.

In order to solve the problems of over enhancement and performance degradation in image enhancement, an image enhancement algorithm based on the local brightness average and global contrast of image is proposed. The algorithm controls the local contrast of image according to the local brightness average of image, and adopts the local and full contrast in global part. The local contrast ratio is the gamma value of the power transformation. Firstly, the image is divided into two parts: low pass filter and high pass filter. The low pass filter controls the amplitude of high pass filter to increase the local contrast. Then′ the low-pass component is modified in a non-linear way and fused with the processed high-pass component. In the contrast experiment, the clarity of the algorithm proposed in this paper is 99% higher than that of the suboptimal algorithm, and the root mean square error(RMSE) is 16% higher. In the process of image enhancement, this algorithm can improve the definition of image, enrich the details of image, and meet the requirements of stability, robustness and high definition of image enhancement algorithm.