Research on Virtual Color Restoration of Complex Building System Based on Discrete Wavelet Transform

At present, image restoration has become a research hotspot in computer vision. The purpose of digital image restoration is to restore the lost information of the image or remove redundant objects without destroying the integrity and visual effects of the image. The operation of user interactive color migration is troublesome, resulting in low efficiency. And, when there are many kinds of colors, it is prone to errors. In response to these problems, this paper proposes automatic selection of sample color migration. Considering that the respective gray-scale histograms of the visual source image and the target image are approximately normal distributions, this paper takes the peak point as the mean value of the normal distribution to construct the objective function. We find all the required partitions according to the user’s needs and use the center points in these partitions as the initial clustering centers of the fuzzy C-means (FCM) algorithm to complete the automatic clustering of the two images. This paper selects representative pixels as sample blocks to realize automatic matching of sample blocks in the two images and complete the color migration of the entire image. We introduced the curvature into the energy functional of the p-harmonic model. According to whether there is noise in the image, a new wavelet domain image restoration model is proposed. According to the established model, the Euler–Lagrange equation is derived by the variational method, the corresponding diffusion equation is established, and the model is analyzed and numerically solved in detail to obtain the restored image. The results show that the combination of image sample texture synthesis and segmentation matching method used in this paper can effectively solve the problem of color unevenness. This not only saves the time for mural restoration but also improves the quality of murals, thereby achieving more realistic visual effects and connectivity.

Research on Embroidery Feature Recognition Algorithm of Traditional National Costumes Based on Double-Layer Model

In order to improve the visual communication ability of traditional national costume patterns, it is necessary to carry out image texture intelligent matching processing. A traditional national costume embroidery feature recognition algorithm based on a double-layer model is proposed. The traditional national costume pattern texture intelligent information acquisition model under the double-layer model is constructed to carry out texture imaging and feature segmentation of traditional national costume patterns, extract the texture histogram of traditional national clothing pattern and national design language, carry out texture segmentation and automatic matching under the two-layer model according to the histogram distribution, enhance and optimize the texture information of traditional national clothing pattern, extract the edge contour feature points of traditional national clothing pattern, and complete the embroidery feature recognition of traditional national clothing. The experimental results show that the designed recognition algorithm has high integrity and accuracy.

A New Music Teaching Mode Based on Computer Automatic Matching Technology

The rapidly developing computer technology has been extensively applied in music teaching. The computer automatic matching technology supports the automatic generation of randomized teaching contents, providing a good tool to develop the musical thinking of students. This paper tentatively introduces this technology to music teaching, and derives a new music teaching mode. The results show that, computer technology can effectively assist in music teaching; the inclusion of computer technology in music teaching arouses students’ interest in music activities; the application of computer automatic matching technology has improved students’ professional skills, live music performance, as well as music ability. The research results greatly promote the reform of music teaching modes and methods.

Method for automatic antenna matching with transmitter output stage

This work is devoted to the study of automatic antenna tuning units of the short-wave range. Devices of narrowband matching based on discrete sets of reactive elements are considered. A classification of the most frequently used automatic matching methods has been made. The advantages and disadvantages of each method are analyzed. Examples of using different approaches in commercially available devices are given. Particular attention is paid to the calculation method of matching, as the most promising for use in modern communications. Assumptions are made about the reasons for its rare use in serial devices. Circuits have been developed to simulate the influence of parasitic parameters of the components of the matching circuit and the body of the tuning unit on the resulting standing wave ratio when using this method. Based on the simulation results, conclusions were drawn about the reasons for the low quality of the calculation method. As an alternative, a new method of automatic tuning is proposed, combining the advantages of computation and search methods, which is based on modeling the search process using a simulation model. The conditions for its application in automatic antenna tuning units are determined. Acomparative analysis of the features of both the known methods of automatic tuning and the newly proposed one ismade.

Expert Knowledge as Basis for Assessing an Automatic Matching Procedure

The continuous development of machine learning procedures and the development of new ways of mapping based on the integration of spatial data from heterogeneous sources have resulted in the automation of many processes associated with cartographic production such as positional accuracy assessment (PAA). The automation of the PAA of spatial data is based on automated matching procedures between corresponding spatial objects (usually building polygons) from two geospatial databases (GDB), which in turn are related to the quantification of the similarity between these objects. Therefore, assessing the capabilities of these automated matching procedures is key to making automation a fully operational solution in PAA processes. The present study has been developed in response to the need to explore the scope of these capabilities by means of a comparison with human capabilities. Thus, using a genetic algorithm (GA) and a group of human experts, two experiments have been carried out: (i) to compare the similarity values between building polygons assigned by both and (ii) to compare the matching procedure developed in both cases. The results obtained showed that the GA—experts agreement was very high, with a mean agreement percentage of 93.3% (for the experiment 1) and 98.8% (for the experiment 2). These results confirm the capability of the machine-based procedures, and specifically of GAs, to carry out matching tasks.

2021 Census England And Wales: Developing Record Speed Linkage Methods to Produce Outputs in a Year

Introduction2021 will herald the next census in England and Wales. The Office for National Statistics (ONS) have a goal of publishing outputs within one year, 4 months earlier than in 2011. Since we produce estimates rather than counts, the linkage of the 2021 Census to the Census Coverage Survey which comprises ~710,000 person and ~370,000 household records, has to be carried out in record time (eight weeks) whilst maintaining incredibly high accuracy (less than 0.1% false positives and 0.25% false negatives). Objectives and ApproachOur approach is to utilise the ONS Distributed Access Platform to write automated matching algorithms that are both efficient and accurate. These methods use parallelisation to speed things up, active machine learning to iteratively improve our parameters, and associative matching to squeeze every last match out automatically without impairing the accuracy. As in 2011, we will be using clerical matchers to resolve cases that cannot be matched automatically. Speeding up the clerical matching process is imperative. We have therefore developed a pre-search algorithm that takes the hard work out of clerical matching by replacing clerical searching (here’s a record can you find a match?) with clerical resolution (here are two or more records, do they match?). ResultsAs a result of our improvements we estimate that we have increased our automatic matching rates from 70% to 91% for person matching, and from 60% to 95% for household matching, without loss of accuracy. However, the biggest gains in terms of speed are delivered by our pre-search algorithm which, at the current iteration, is limiting false negatives to ~0.13% according to the 2011 gold standard. ConclusionWe estimate that overall our improvements will mean that in 2021 we will need less than half the clerical resource that was required in 2011 and will meet our eight-week deadline.

Validation of the Accuracy of Postoperative Analysis Methods for Locating the Actual Position of Implants: An In Vitro Study

Assessment of the accuracy of an implant guide system is essential, yet the reliability of postoperative methods for locating the implant position has still not been clarified. This study therefore sought to evaluate the accuracy of postoperative methods for locating the actual position of implants in terms of their linear and angular deviations. The implant position in a dentiform model was located using the following three methods: manual matching on a cone-beam computed tomography (CBCT) image (MC group), manual matching on a mesh model of CBCT (MM group), and automatic matching on a scan abutment of a scan image (AS group). Thirty clinicians adopted each method, and the estimated position of the implant in each group was compared three-dimensionally with the reference implant position using image analysis software in terms of the linear, vertical, and angular deviations. One-way analysis of variance (ANOVA) and Tukey’s post-hoc test were used for statistical analyses (α = 0.05). In general, the deviations were the largest in the MC group, followed by the MM group and the AS group. The ANOVA results suggested that all deviations values were markedly smaller in the AS group than in the MC group (p < 0.001). The interoperator measurement variability of all deviations was relatively smaller in the AS group than in the other two groups. The automatic matching method using scan abutments was more accurate than the manual matching methods using CBCT and mesh images in assessing the deviations that existed between the planned and actual positions of the implant. The use of scan abutments is recommended for the postoperative assessment of an implant’s placement location.