Defined as a visual inhomogeneity, Mura can cause seriously unpleasant feelings and that’s why it needs to be inspected. Band Mura, which has a large area, is particularly difficult to be detected because of its irregular shape and size as well as its low contrast. So we propose a UADD-GAN model to detect band Mura in this work. Consisting of a proposed UADD generator and a discriminator, the model is trained with some normal samples, after which the generator is able to simulate the distribution of normal samples. During training, the generator takes normal images as inputs and output their reconstructions, while the discriminator receives images and determines whether they’re true or fake, defiantly helping the generator to perform reconstructions better. The symmetric structure and operation of skipadding make it easy for the UADD generator to reconstruct the normal samples well. On the contrary, the generator performs worse in the reconstruction of Mura samples so that we can distinguish them from the normal ones. In addition, we use multiple feature layers of the discriminator for supervision instead of using only the classification layer, helping the generator to reconstruct normal samples better. We’ve conducted experiments of MURA data sets with different proportion and our research indicates that the proposed model surpass other state of the art methods.
By exploiting those novel transport phenomena at nanoscale, the nanochannel system has shown electrically maneuverable conductance, suggesting the potential usage as neuromorphic devices. However, several critical features of biological synapses, i.e., the memorable and gradual conductance modulation, were seldom reported in the system. In this work by imposing room-temperature ion liquid (IL) and KCl solution into the two ends of nanochannel system, we demonstrate that this electrical manipulation of nanochannel conductance becomes nonvolatile and capable of mimicking the analog behaviors of synapses. The mechanism of gradual conductance tuning is identified as the voltage-induced movement of the interface between the immiscible RTIL and KCl solution according tofluorescencetechnique.
Considering actual industrial production, precise positioning for irregularly shaped workpiece is required. If the workpiece is located by the method of machine vision, the critical step is to get the position of workpiece contour in image. However the edge information quality in image can be affected by workpiece shape, material, lighting method and other factors. Especially for the complex edge information, the traditional edge detection algorithm is usually hard to eliminate the noise points near the true edge, these noise points will be misjudged as true edge points, which will reduce the accuracy of the contour positioning results. In this paper, a precise contour positioning method for workpiece with irregular shape was proposed. Firstly, based on the initial results of template matching, edge detection region with variable size according to the edge normal direction was created, then a set of edge points can be obtained. Secondly, according to the correlation between true edge points, the position deviation of each point was calculated, and the edge point evaluation function was defined by combining gradient amplitude and position deviation. Finally, removing the points with lower defined scores to obtain final set of edge points, which determines the position of workpiece contour in image. The experiments show that this method can effectively exclude noise points in edge point set, obtain the true contour of workpiece with any shape, and overcome the shortcomings that the traditional edge detection algorithm is greatly influenced by edge noise. The method has high accuracy, stability and strong practicality.
An automatic registration method for Surface Mount Technology (SMT) stencil image is proposed. During the registration, the minimum bounding rectangle(MBR) of the Stencil changes with the stencil’s arbitrary placement and angle, while the absolute minimum distance between the registration feature point and the rectangle vertex remains unchanged. This character can be used to solve the random error and failure rate in stencil placement. With three feature points in standard Gerber data image and in stencil image, the affine transformation is carried out. After mapping the coordinate systems of the Gerber image and the stencil image are consistent with each other. Then the internal automatic matching test and secondary registration are introduced to improve the accuracy. The results of experiment show that this method can significantly improve the efficiency and intelligence level of SMT.
Nowadays, more and more underwater electricity or communication cables and oil or gas pipelines have been installing. Equipment aging and damages to them have caused series of accidents, resulting in huge economic loss and environmental pollution. This paper proposes a long distance underwater linear object detection method based on range-gated optical imaging, which can help the maintenance and inspections of underwater cables and pipelines. The whole object detection algorithm can be divided into three stages: image enhancement, edge detection and object detection. In the image enhancement step, The system deals with the low contrast, blur and noises characteristics of underwater images by means of contrast normalization, median filtering, wavelet transform, and finally gets high quality images. Then, the Canny operator was used to extract object's edge features. Finally, for the emergence of noise edges, a robust algorithm named Random Sample Consensus was chosen to accurately detect linear object and estimate its parameters such as position and direction. This algorithm has been tested on the experimental data in the boat tank of Huazhong University of Science and Technology, collected with a range-gated imaging system. The results show that the algorithm can effectively detect underwater curved-linear objects, with the detection rate achieving 96%, and the effective detection range can be up to 5 times the length of the underwater decay.
Sizing a small particle from its scattered field has been a long-standing problem. Popular established methods require a priori knowledge of either the refractive index of the particle, or the approximate particle size range. In this paper, the diffraction tomography (DT) theory is studied and a single particle sizing approach using angular optical scattering field is proposed. There is a Fourier relationship between the scattering amplitude in the far zone and the scattering potential of the scatterer, under the 1st-order Born approximation for weakly scattering. Based on this relationship, the distribution of scattering potential can be retrieved from angular resolved scattered field by the use of a fast Fourier transform. Single particle size is estimated from the scattering potential. Numerical simulations for spherical particles are presented and discussed. Simulation results show that in the case of low contrast, the size of the particles can be estimated accurately in the presence of moderate noise. A further variant of this algorithm based on Rytov approximation is also discussed.
We present a fast, simple, sub-pixel algorithm on the critical angle refractometer to measure the refractive index of the liquid sample by determining the centroid of the light intensity of the relative reflective curve. The centroid algorithm utilizes a divergent fiber-coupled royal blue LED source to irradiate on the dielectric surface between the prism and the media, which generates the light intensity distribution of the reflectance facula. Instead of the critical angle pixel as the differential algorithm and the threshold algorithm, the sub pixel centroid algorithm is based on calculating the centroid value of the light intensity of the relative reflective curve. In some moderate turbid solutions, the centroid algorithm is less sensitive to the scattering and absorption than the differential algorithm and the threshold algorithm. It is possible to utilize the centroid point of the relative reflective curve to determine the refractive index. Supported by the theoretical analysis and experimental results on saline solutions, we can conclude that the proposed algorithm is effective to get the super resolution and meaningful to the refractive index measurement of the liquid. The critical angle refractometer with this centroid method is potential to be a high-accuracy, high-resolution, and reliable automatic refractometer.
An improved calibration method for digital Abbe refractometer is proposed. Based on Fresnel reflection theory, digital
Abbe refractometer measures the index of refraction by processing bright-dark pattern images. For extreme environment
applications, our team has developed a digital Abbe refractometer. By analyzing bright-dark pattern images, it shows
optical aberration may reduce positioning accuracy on critical angle. The main work of this paper is to propose a new
calibrate method for digital Abbe refractometer. An optical system is built to simulate the refractometer. A motorized
micropositioning stage is inserted to precisely control the position of bright-dark boundary. An area CCD captures an
image each time boundary displaced. Get the boundary through entire measuring range to form an image database. The
database indicates the corresponding relations between bright-dark pattern image acquired by CCD camera and boundary
position read by motorized stage. When measuring the refractive index of liquid, match its bright-dark pattern image to
images in database, and get the boundary position from the nearest match. Compared to the former method of computing
boundary position from images with aberration, the proposed method calibrate refractometer by large amount of
experimental data, thus improve stability of the measurement.