最新刊期
期 6 ， 2020
- 摘要：Factor optimization was carried out on Flicker performance, especially on the research of material related factors, the performance of the Flicker is improved and finally the overall cross-order is increased. By evaluating and optimizing the flicker performance of the TFT-LCD panel, including the establishment of evaluation methods, the performance simulation and sample performance measurement, the convergence performance optimization direction is finally combined with the experimental product test and verification, then the optimization direction of panel flicker performance improvement is proposed. Compared with the optimization of conventional electrical properties, including device leakage and device capacitance (Cst), the research content of this article focuses more on the optimization of the material perspective, specifically the optimization of the response time parameters of the liquid crystal, and the main research methods are simulation of flicker performance of liquid crystals with different response times, actual performance measurement and brightness detection. It is found that the LCD response time parameter is increased from 8 ms to 10 ms, and the effective cross-order of its products from 8 to 10 orders, so as to effectively improve the flicker of the product cross-order. The panel can improve the flicker performance of the panel by optimizing the response time parameters of the liquid crystal material.关键词：flicker;liquid crystal response time;cross-order
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发布时间：2020-07-13 - 摘要：In order to improve the image quality and product yield of photo alignment products, this paper systematically studies the bad phenomenon of image jitter in low gray scale of photo alignment products, finds out the mechanism of abnormal image jitter, and finds effective improvement measures. Firstly, the abnormal position pre-tilt angle is determined by comparing the pre-tilt angle of the abnormal area with the box thickness gauge. Secondly, through the correlation analysis of photo alignment principle and pre-tilt angle, the mechanism of image jitter is reasonably explained, and the local optical orientation voltage anomaly caused by external electrostatic field is confirmed. Finally, the electrostatic generating unit is confirmed by the investigation mechanism, and effective improvement measures are proposed. The image jitter is the static electricity in the process of the base plate. Accumulation results in a certain charge accumulated on the back of the substrate. Under the influence of the external electrostatic field, the voltage in the pixel does not reach the predetermined value, resulting in an abnormal pre-tilt angle and image jitter. By improving the electrostatic accumulation in the process, the abnormal light orientation voltage caused by electrostatic accumulation on the back of the substrate can be prevented, improving poor image jitter.关键词：photo alignment;low gray image jitter;static electricity
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发布时间：2020-07-13 - 摘要：A series of liquid crystal (LC) polymers (P1~P7) were synthesized by grafting with nematic flexible monomer 4-(undec-10-enoyloxy) phenyl 4-ethoxybenzoate (M1) and cholesteric monomer cholesteryl allyloxybenzoate (M2) to polymethyl hydrosiloxane (PMHS). The chemical structures and properties of the monomers and copolymers were investigated by means of fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance hydrogen spectrometer (1HNMR), differential scanning calorimetry (DSC), polarised optical microscopy (POM), X-ray diffraction (XRD), thermogravimetric analysis (TGA) and polarimeter. The analyses show that P1~P6 are cholesteric LC polymers, except that P7 is a nematic LC polymer. The introduction of nematic flexible monomer M1 did not change the cholesteric phase. The introduction of M1 together with the soft siloxane main chain play a role in reducing the glass transition temperature (P 5 and P6 show LC state at room temperature), widening the LC range, stabilizing the LC phase and reducing the cost, which is beneficial to the application of LC polymers.关键词：chiral side-chain liquid crystal polymer;cholesteric phase;graft copolymerization
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发布时间：2020-07-13
Materials and Devices
- 摘要：Aiming at the high error caused by the integral method for the traditional optical power meter, from the application point of view, a high-precision optical power meter with MSP430 is proposed. The photoelectric sensor converts the light signal into mA current signal, through a negative feedback current amplification, and then through a differential amplification and filtering circuit, and converts anolog signal into a digital signal through a 24-bit high-precision AD chip. The optical power is calculated using recursive and median digital filter. The measured value is displayed on the LCD. The optical power curve is also displayed after through the Savitzky-Golay filter in measurement phase. The experiment proves that the optical power meter has an error of less than 0.3%, low power consumption, stable system, friendly display interface, it can store measurement data and display optical power curve.关键词：low power consumption;24-bit high-precision;digital filter;power curve
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发布时间：2020-07-13 - 摘要：A non mechanical beam steering system with light addressed liquid crystal spatial light modulator(LCSLM) is proposed and designed to resolve the problem of two-dimensional laser beam splitting and muti-beam deflection, which can control the direction and intensity of each beam separately with only one LCSLM. The generation process and simulation of the phase template of multi-beam programmable control is realized by G-S phase iterative algorithm. Firstly, the sub-aperture method is used to generate the required phase distribution as the initial value. Then, the G-S phase iterative algorithm is used to optimize the phase distribution, so that the phase distribution in each sub-aperture is gradually extended to the entire phase template. An improved G-S phase iterative algorithm is proposed. Finally, the inverse phase simulation of the calculated phase distribution is performed. The simulation results show that the proposed multi-beam two-dimensional deflection algorithm can meet the application needs, and the diffraction efficiency of multiple beams is enhanced and the root mean square error of the beam is reduced.关键词：G-S phase iterative algorithm;Liquid crystal spatial light modulator;multiple beams steering;phase modulation
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发布时间：2020-07-13 - 摘要：Existing mobile terminal segmentation network has problems such as poor segmentation accuracy and segmentation edge blurring. To this end, a lightweight portrait segmentation network that incorporates attention mechanisms is proposed. Firstly, the image features are extracted by MobileNetV2 network. Then, the attention module NLNet (Non-local neural networks) is lightened, and then the optimized attention module is embedded in the four-layer decoding network. The decoding network with attention mechanism adaptively learns the effective features, and finally obtains the portrait segmentation result map through SoftMax. At the same time, the loss function is improved, and Multi-Loss (multi-loss function) is introduced to make the network easier to converge. The way of attention mechanisms fused in decoding networks makes the lightweight network achieve better results in the semantic segmentation task. Experimental results show that the model achieves 92.29% MeanIOU on the 550 self-collected portrait test set, and the split time of the single picture on the Inter(R) Core i5 CPU is 0.74 s. Compared with the traditional portrait segmentation network, the research network has obvious advantages in segmentation precision and segmentation speed, and is suitable for mobile devices.关键词：portrait segmentation;attention mechanism;lightweight;convolutional neural network
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发布时间：2020-07-13 - 摘要：Combining global features and local features is one way to improve person re-identification accuracy. Existing algorithms usually extract features from specific semantic regions of the human body. Since the human body structure is not taken into account, the learning difficulty is increased, and the efficiency and robustness are poor in the scenes with large differences. In order to solve the above problems, this paper proposes a person re-identification algorithm based on multi granularity feature fusion, which combines global feature, local feature and human structure feature. The algorithm does not introduce any prior knowledge of human body structure. In terms of feature extraction, the average pooling and maximum pooling are used to weight the feature map to obtain strong global features. Local features are obtained by slicing the feature map. Based on the original local features, local relative features are introduced as human structural features. In terms of metrics, a multi-level supervision mechanism with triple loss and ID loss at different scales is used. Experiments on Market1501 and DukeMTMC-reID show that the Rank-1 index of the algorithm is 1.3% and 3.9% higher than Part-based Convolutional Baseline(PCB) method, and the mean Average Precision(mAP) is 5.1% and 9.8% higher than PCB method.关键词：global feature;local feature;human structural feature;feature fusion;deep learning;convolutional neural network;person re-identification
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发布时间：2020-07-13 - 摘要：The TFT manufacturing process can inevitably result in a number of process defects, it is necessary to individually determine the impact caused by the defects. This defect inspection method requires a lot of manpower and slow, low accuracy. Therefore, it is especially important to replace manual recognition with computerized automatic identification. A key part in automatic identification is to locate the TFT circuit. Aiming at the problem that the existing image processing algorithms can not accurately locate the position of the TFT circuit due to the defect color, shape, position and size unfixed. This paper proposes an image reconstruction algorithm based on autocorrelation and template matching. Firstly, the region extraction is performed on the defect image acquired by the automated optical inspection(AOI) camera, and estimates the angle and corrects the image. The circuit's repetition period is estimated according to the autocorrelation estimation function of the gray-scale vertical response of the edge image, and then the periodic gray-scale mean is used to determine the position of a group of longitudinal lines, and the remaining vertical lines are reconstructed by using the periodic characteristics of the TFT circuit. Finally, the silicon island part of the TFT circuit is reconstructed by the angular template matching algorithm. The experimental results show that the proposed algorithm can reconstruct the circuit under the condition of defect occlusion, blurred picture, and missing circuit. The accuracy of positioning is over 96%. Basically, it can meet the circuit segmentation requirements in TFT defect auto-identification.关键词：TFT defect circuit;image segmentation;autocorrelation;template matching;image reconstruction
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发布时间：2020-07-13 - 摘要：Feature extraction is performed on a convolutional neural network using only the same size image and convolution kernel, which results in incomplete extraction features. In the traffic sign recognition, the continuous change of the position between the vehicle camera and the traffic sign affects the recognition accuracy of the traffic sign. A traffic sign recognition method based on multi-scale feature fusion and extreme learning machine is proposed. Firstly, the network model adapted to three different size images is pre-trained as the initial model of the experiment. Then, the three network models are combined to construct a multi-scale convolutional neural network, and the parameters of the three pre-trained networks are cascaded to the full connection of the fusion model to train the fully connected layer of the fusion model, and the network parameters are updated by the random gradient descent algorithm. Finally, the fusion model is used as the feature extractor to extract features, which are sent to the extreme learning machine(ELM) to realize traffic sign recognition. The experimental results show that the recognition accuracy of the multi-scale feature fusion and extreme learning machine combined network is 99.23% and the recognition speed is 46 ms. Compared with the pre-trained network, the classification accuracy of the network is increased by 2.35%, 3.22% and 3.74%, respectively. Therefore, the multi-scale feature fusion method can effectively extract the feature information of traffic sign images, ELM classifier can improve classification accuracy and classification time, and meet the requirements of traffic sign recognition accuracy and real-time.关键词：convolutional neural network;identification of traffic signs;multi-scale fusion;intelligent transportation;extreme learning machine
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发布时间：2020-07-13 - 摘要：Aiming at the situation that the target deformation, occlusion and scale variation lead to tracking failure, an improved multi-feature fusion target tracking algorithm is proposed. Firstly, the fusion weights of the two features are obtained by calculating the difference between the two adjacent PSRs of the HOG(Histogram of Oriented Gridients) and CN(Color Names), and the HOG and the CN are adaptively fused by using the obtained weights. The response obtained by the first merged response and the color histogram feature is secondarily fused with a fixed weight, and the target center position is determined according to the fusion result. Then, the learning rate of the position correlation filter and the scale correlation filter is dynamically adjusted by the difference between the PSR(Peak-to-Sidelobe Ratio) of the response and its mean value. Finally, the experimental verification is performed on the OTB50 standard dataset, and compared with other algorithms. The results show that the proposed algorithm outperforms other algorithms in many performance indicators. The accuracy is 81.9%, and the success rate is 61.1%. It can effectively adapt to target tracking under deformation, occlusion and scale variation scenarios.关键词：target tracking;multi-feature fusion;adaptive update
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发布时间：2020-07-13 - 摘要：To quickly and efficiently implement a color interpolation algorithm on the FPGA platform and get a high-quality color image, an improved color interpolation algorithm is designed and implemented using Xilinx high-level synthesis tool HLS. The algorithm combines the bilinear interpolation algorithm and first-order differential edge oriented interpolation algorithm to complete image color interpolation. The first-order differential edge oriented interpolation algorithm is used to calculate the missing color components for the pixels with R component and B component as the center pixel points, and the bilinear interpolation algorithm is used to calculate the missing color components for the pixels with G component as the center pixel points. The algorithm fully considers image edge interpolation and FPGA hardware resources, which can restore a Bayer format image and restore full-color image. Compared with the traditional FPGA development, this paper uses HLS to shorten the development cycle and improve development efficiency. The experimental results on the Kodak dataset show that the color peak signal-to-noise ratio (CPSNR) of the improved color interpolation algorithm is 4~6 dB higher than that of the conventional algorithm, and the image aliasing and edge blur are reduced. This algorithm takes up less FPGA resources and can realize real-time image color interpolation.关键词：color interpolation;Vivado HLS;FPGA;hardware acceleration
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发布时间：2020-07-13 - 摘要：By introducing the group sparse representation of strip noise into the single variation model, a single variational model restricted by group sparse technique is proposed to remove noise. The proposed model is solved by alternating direction method of multipliers. The experiments show that the proposed model can more effectively use the similarities between strip noise to remove noise compared with other existing models, and it can reconstruct the image information better. The values of peak signal-to-noise ratio and structural similarity are increased by 6.76 dB and 0.25, respectively, which shows good image denoising performance of our model.关键词：strip noise;variation;group sparse;alternating direction method of multipliers
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发布时间：2020-07-13 - 摘要：In order to optimize the static image registration algorithm in video registration, a static image registration algorithm based on deep learning convolutional neural network VGGNet is proposed. The simulation experiments results show that VGGNet can be well applied to the static image registration work. Combining the root mean square error and Nred results, it can be seen that the static image registration algorithm based on the output features of Conv5, FC1, or FC2 has good performance. The algorithm based on FC2 has the best performance with root mean square error value of 0.031 22 and Nred of 74. After video scaling and brightness conversion, the performance of the static image registration algorithm decreases. The performance of the registration algorithm based on FC2 is better overall after the brightness conversion. Compared with the traditional image registration algorithm based on HOG and LBP feature extraction, this algorithm has better registration precision and accuracy. The research results can provide a reference for current static image registration algorithms based on deep learning convolutional neural networks.关键词：video;image registration;deep learning;VGGNet
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发布时间：2020-07-13 - 摘要：The traditional medical image retrieval uses a single image, but the image information in a single image is limited, and the medical images taken from different angles can not be effectively utilized. To solve this problem, a medical image retrieval method based on multi-view metric learning with Fisher discriminant analysis (MVML-FDA) is proposed. The MVML-FDA learns robust metric space from multiple views based on Fisher discriminant model. A robust metric space allows the medical images of the same class to be closely mapped in the metric space, and different classes of medical images are separated from each other as much as possible. At the same time, the view weighting factor is set to make full use of the different representation information of each view feature. According to the distance metric learning, the MVML-FDA is applied to the diagnosis of breast diseases. The experimental results on the Breast Cancer Digital Repository dataset show that the proposed method has better performance, and improves retrieval accuracy by 7% compared with four multi-view methods.关键词：medical image retrieval;breast image;multi-view;distance metric learning
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发布时间：2020-07-13
Image Processing
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