The Construction of PLA Image in China’s Official Discourse From the Perspective of Positive Discourse Analysis——Based on Government Work Reports Over the Last 15 Years

Government Work Report is essential for domestic and international understanding of China’s national conditions.This paper selects the national defense section in Government Work Reports released by the State Council of the People’s Republic of China over the last fifteen years from 2009 to 2023 as an example of China’s official discourse.From the perspective of positive discourse analysis,the theory of three meta-functions of language proposed by M.A.K.Halliday in Systemic Functional Linguistics is used in this article in terms of transitivity,appraisal,mood,modality,and theme to explore the constructing of the People’s Liberation Army(PLA)image.This study finds that,by using the goals and circumstances with optimistic meaning in material processes,adopting more appreciation in attitude,applying more declaratives in mood,utilizing modal operators with high modulation,and implicit objective modal adjuncts,and employing government-focused themes,China’s official discourse objectively and authentically conveys a positive image of the brave and just PLA both at home and abroad which advocates itself to peace-keeping,and mission-fulfilling.

Using shapes correlation for active contour segmentation of uterine fibroid ultrasound images in computer-aided therapy

Segmenting the lesion regions from the ultrasound （US） images is an important step in the intra-operative planning of some computer-aided therapies. High-Intensity Focused Ultrasound （HIFU）, as a popular computer-aided therapy, has been widely used in the treatment of uterine fibroids. However, such segmentation in HIFU remains challenge for two reasons： （1） the blurry or missing boundaries of lesion regions in the HIFU images and （2） the deformation of uterine fibroids caused by the patient＇s breathing or an external force during the US imaging process, which can lead to complex shapes of lesion regions. These factors have prevented classical active contour-based segmentation methods from yielding desired results for uterine fibroids in US images. In this paper, a novel active contour-based segmentation method is proposed, which utilizes the correlation information of target shapes among a sequence of images as prior knowledge to aid the existing active contour method. This prior knowledge can be interpreted as a unsupervised clustering of shapes prior modeling. Meanwhile, it is also proved that the shapes correlation has the low-rank property in a linear space, and the theory of matrix recovery is used as an effective tool to impose the proposed prior on an existing active contour model. Finally, an accurate method is developed to solve the proposed model by using the Augmented Lagrange Multiplier （ALM）. Experimental results from both synthetic and clinical uterine fibroids US image sequences demonstrate that the proposed method can consistently improve the performance of active contour models and increase the robustness against missing or misleading boundaries, and can greatly improve the efficiency of HIFU therapy.

Using shape contexts method for registration of contra lateral breasts in thermal images

AIM: To achieve symmetric boundaries for left and right breasts boundaries in thermal images by registration. METHODS: The proposed method for registration consists of two steps. In the first step, shape context, an approach as presented by Belongie and Malik was applied for registration of two breast boundaries. The shape context is an approach to measure shape similarity. Two sets of finite sample points from shape contours of two breasts are then presented. Consequently, the correspondences between the two shapes are found. By finding correspondences, the sample point which has the most similar shape context is obtained. RESULTS: In this study, a line up transformation which maps one shape onto the other has been estimated in order to complete shape. The used of a thin plate spline permitted good estimation of a plane transformation which has capability to map unselective points from one shape onto the other. The obtained aligningtransformation of boundaries points has been applied successfully to map the two breasts interior points. Some of advantages for using shape context method in this work are as follows:(1) no special land marks or key points are needed;(2) it is tolerant to all common shape deformation; and(3) although it is uncomplicated and straightforward to use, it gives remarkably powerful descriptor for point sets significantly upgrading point set registration. Results are very promising. The proposed algorithm was implemented for 32 cases. Boundary registration is done perfectly for 28 cases.CONCLUSION: We used shape contexts method that is simple and easy to implement to achieve symmetric boundaries for left and right breasts boundaries in thermal images.

Shape characterization of sand particles based on digital image processing technology

To characterize the shape of sand particles for concrete,a new method is proposed based on digital image processing(known as the DIP method).By analyzing sand particles projection,the length,width and thickness of sand were measured to characterize particle form.The area and perimeter were measured to characterize particle angularity.The results of the DIP method and Vernier caliper were compared to examine the accuracy of the DIP method.The sample size test was conducted to show the statistical significance of shape results measured by the DIP method.The practicality of the DIP method was verified by instance analysis.The results show that aspect ratios and roundness measured by the DIP method are equal to ones by the Vernier caliper.Results by DIP are dependent on the sand particle number,and at least 350 particles should be measured to represent the overall shape property of sand.The results show that the DIP method is able to distinguish the differences in the shape of sand particles.It achieves the direct measurement of sand particle thickness,and the characterization results of sand aspect ratios and roundness are accurate,statistically significant and practical.Therefore,the DIP method is suitable for sand particle shape characterization.

Multi-sensor image registration using multi-resolution shape analysis

Multi-sensor image registration has been widely used in remote sensing and medical image field, but registration performance is degenerated when heterogeneous images are involved. An image registration method based on multi-resolution shape analysis is proposed in this paper, to deal with the problem that the shape of similar objects is always invariant. The contours of shapes are first detected as visual features using an extended contour search algorithm in order to reduce effects of noise, and the multi-resolution shape descriptor is constructed through Fourier curvature representation of the contour’s chain code. Then a minimum distance function is used to judge the similarity between two contours. To avoid the effect of different resolution and intensity distribution, suitable resolution of each image is selected by maximizing the consistency of its pyramid shapes. Finally, the transformation parameters are estimated based on the matched control-point pairs which are the centers of gravity of the closed contours. Multi-sensor Landsat TM imagery and infrared imagery have been used as experimental data for comparison with the classical contour-based registration. Our results have been shown to be superior to the classical ones.

Evolutionary Computation Based Optimization of Image Zernike Moments Shape Feature Vector

The image shape feature can be described by the image Zernike moments. In this paper, we points out the problem that the high dimension image Zernike moments shape feature vector can describe more detail of the original image but has too many elements making trouble for the next image analysis phases. Then the low dimension image Zernike moments shape feature vector should be improved and optimized to describe more detail of the original image. So the optimization algorithm based on evolutionary computation is designed and implemented in this paper to solve this problem. The experimental results demonstrate the feasibility of the optimization algorithm.

A method of automatic shape depiction and information extraction for oceanic eddies in SAR images

Synthetic aperture radar （SAR） provides a large amount of image data for the observation and research of oceanic eddies. The use of SAR images to automatically depict the shape of eddies and extract the eddy information is of great significance to the study of the oceanic eddies and the application of SAR eddy images. In this paper, a method of automatic shape depiction and information extraction for oceanic eddies in SAR images is proposed, which is for the research of spiral eddies. Firstly, the skeleton image is got by the skeletonization of SAR image. Secondly, the logarithmic spirals detected in the skeleton image are drawn on the SAR image to depict the shape of oceanic eddies. Finally, the eddy information is extracted based on the results of shape depiction. The sentinel 1 SAR eddy images in the Black Sea area were used for the experiment in this paper. The experimental results show that the proposed method can automatically depict the shape of eddies and extract the eddy information. The shape depiction results are consistent with the actual shape of the eddies, and the extracted eddy information is consistent with the reference information extracted by manual operation. As a result, the validity of the method is verified.

Significance of including lid thickness and particle shape factor in numerical modeling for prediction of particle trap efficiency of invert trap

Sediment accumulation on the bed of open sewers and drains reduces hydraulic efficiency and can cause localized flooding.Slotted invert traps installed underneath the bed of open sewers and drains can eliminate sediment build-up by catching sediment load.Previous three-dimensional(3D)computational studies have examined the particle trapping performance of invert traps of different shapes and depths under varied sediment and flow conditions,considering particles as spheres.For two-dimensional and 3D numerical modeling,researchers assumed the lid geometry to be a thin line and a plane,respectively.In this 3D numerical study,the particle trapping efficiency of a slotted irregular hexagonal invert trap fitted at the flume bottom was examined by incorporating the particle shape factor of non-spherical sewage solid particles and the thicknesses of upstream and downstream lids over the trap in the discrete phase model of the ANSYS Fluent 2020 R1 software.The volume of fluid(VOF)and the realizable k-turbulence models were used to predict the velocity field.The two-dimensional particle image velocimetry(PIV)was used to measure the velocity field inside the invert trap.The results showed that the thicknesses of upstream and downstream lids affected the velocity field and turbulent kinetic energy at all flow depths.The joint impact of the particle shape factor and lid thickness on the trap efficiency was significant.When both the lid thickness and particle shape factor were considered in the numerical modeling,trap efficiencies were underestimated,with relative errors of-8.66%to-0.65%in comparison to the experimental values of Mohsin and Kaushal(2017).They were also lower than the values predicted by Mohsin and Kaushal(2017),which showed an overall overestimation with errors of-2.3%to 17.4%.

Parametric shape prior model used in image segmentation

Due to the frequency of occlusion, cluttering and lowcontrast edges, gray intensity based active contour models oftenfail to segment meaningful objects. Prior shape information is usuallyutilized to segment desirable objects. A parametric shape priormodel is proposed. Firstly, principal component analysis is employedto train object shape and transformation is added to shaperepresentation. Then the energy function is constructed througha combination of shape prior energy, gray intensity energy andshape constraint energy of the kernel density function. The objectboundary extraction process is converted into the parameters solvingprocess of object shape. Besides, two new shape prior energyfunctions are defined when desirable objects are occluded by otherobjects or some parts of them are missing. Finally, an alternatingdecent iteration solving scheme is proposed for numerical implementation.Experiments on synthetic and real images demonstratethe robustness and accuracy of the proposed method.

Human Plantar Pressure Image and Foot Shape Matching

Medical doctors and podiatrists have been using plantar pressure for the evaluation of the foot loading in regard to foot biomechanics and foot health for decades. High plantar pressure can cause pain and foot injury such as plantar ulcer during walking. Two types of systems are suitable for pressure capture and they are commonly known as floor mat or floor pad and in-shoe pad. For the floor-mat system pressure values are displayed as image which does not depict the foot shape. Therefore, shortcoming of this system for plantar pressure recording during walking is that the location of the pressure value related to the plantar surface is only approximate. A research was conducted to determine whether markers can be placed on the plantar surface and their positions identifiable on the pressure image. This paper describes the technique for matching the plantar shape to the pressure image during walking.

Analysis of Object Depth Effects on Accuracy of Dimensional Shape in X and Y Directions Using Single Non-metric Image

In general, to reconstruct the accurate shape of buildings, we need at least one stereomodel （two photographs） for each building. In most cases, however, only a single non-metric photograph is available, which is usually obtained either by an amateur, such as a tourist, or from a newspaper or a post card. To evaluate the validity of 3D reconstruction from a single non-metric image, this study analyzes the effects of object depth on the accuracy of dimensional shape in X and Y directions using a single non-metric image by means of simulation technique, as this was considered to be, in most cases, a main source of data acquisition in recording and documenting buildings.

A DESCRIPTION METHOD FOR ARBITRARILY SHAPED AND SIZED GRANULES IN 2D IMAGE

An alternative method is proposed in this letter for describing the arbitrary shape and size for granules in 2D image.After image binarization, the edge points on contour are detected, by which the centroid of the shape in question is sought using the moment calculation.Using Principal Component Analysis(PCA), the major and minor diameters are computed.Based on the signature curve-fitting, the first-order derivative is taken so as to seek all the characteristic vertices.By connecting the vertices found, the simplified polygon is formed and utilized for shape and size descriptive purposes.The developed algorithm is run on two given real particle images, and the execution results indicate that the computed parameters can technically well describe the shape and size for the original particles, being able to provide a ready-to-use database for machine vision system to perform related data processing tasks.

Shape recovery using high dynamic range images

An effective method for object shape recovery using HDRIs （high dynamic range images） is proposed. The radiance values of each point on the reference sphere and target object are firstly calculated, thus the set of candidate normals of each target point are found by comparing its radiance to that of each reference sphere point. In single-image shape recovery, a smoothness operation is applied to the target normals to obtain a stable and reasonable result; while in photometric stereo, radiance vectors of reference and target objects formed due to illuminations under different fight source directions are directly compared to get the most suitable target normals. Finally, the height values can be recovered from the resulting normal field. Because diffuse and specular reflection are handled in an unified framework with radiance, our approach eliminates the limitation presented in most recovery strategies, i.e., only Lambertian model can be used. The experiment results from the real and synthesized images show the performance of our approach.

Study on Chinese National Image Shaping Under The Background of Rapid Growth of Outbound Tourism of Citizens

The national image is multi-dimensional, outbound tourism is one of the most intuitive ways. The outbound tourism behavior of Individual citizen is not only considered as the outward manifestation of individual civil quality, but also considered as the emblem the quality of all citizens of whole country, affects the national image, related to the country＇s national influence and credibility. The outbound tourism of Chinese citizens brought about the rapid growth of the enormous economic benefits and influence, which makes the outbound tourism behavior of Chinese citizens gotten more concern. The uncivilized outbound tourism behavior of Chinese citizens are frequent, which brings extremely strong damage, and which serious impact on the healthy image about the Ancient civilization and the country of ceremonies of China, and which greatly restricts the spread of a good national image of China. Based on the analysis about the characteristics of rapid growth outbound tourism of Chinese citizens, this paper discusses the approaches of current Chinese national image shaping, put forward that China must strengthen citizen education, and improve relevant laws and regulations, and strengthen supervision, only then might Chinese citizens outbound tourism uncivilized behavior be prevented from the root.

Digital Image Correlation Using Specific Shape Function for Stress Intensity Factor Measurement

The stress intensity factor (SIF) is a critical parameter associated with the fracture behaviour of materials. In this paper, we select the displacement function around a crack tip as the shape function of the digital image correlation (DIC), which makes it possible to directly calculate the SIF by the correlation scheme. Moreover, we use a non-rectangular subset, which can reduce the influence of plastic deformation and crack width on the DIC measurement accuracy. We measured the SIF of a mode I crack in a super-hard aluminium alloy specimen to verify the performance of the proposed method. Our experimental results show that a DIC with a specific shape function can be used to accurately and efficiently calculate the SIF. Furthermore, we also present a practical application of our proposed method for determining the SIF, crack propagation angle and crack tip displacement. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg.

Detection of broken manhole cover using improved Hough and image contrast

The damage or loss of urban road manhole covers may cause great risk to residents＇ lives and property if they cannot be discovered in time. Most existing research recommendations for solving this problem are difficult to implement. This paper proposes an algorithm that combines the improved Hough transform and image comparison to identify the damage or loss of the manhole covers in complicated surface conditions by using existing urban road video images. Focusing on the pre-processed images, the edge contour tracking algorithm is applied to find all of the edges. Then with the improved Hough transformation, color recognition and image matching algorithm, the manhole cover area is found and the change rates of the manhole cover area are calculated. Based on the threshold of the change rates, it can be determined whether there is potential damage or loss in the manhole cover. Compared with the traditional Hough transform, the proposed method can effectively improve the processing speed and reduce invalid sampling and accumulation. Experimental results indicate that the proposed algorithm has the functions of effective positioning and early warning in the conditions of complex background, different perspectives, and different videoing time and conditions, such as when the target is partially covered.

Flame image recognition of alumina rotary kiln by artificial neural network and support vector machine methods

Based on the Fourier transform, a new shape descriptor was proposed to represent the flame image. By employing the shape descriptor as the input, the flame image recognition was studied by the methods of the artificial neural network(ANN) and the support vector machine(SVM) respectively. And the recognition experiments were carried out by using flame image data sampled from an alumina rotary kiln to evaluate their effectiveness. The results show that the two recognition methods can achieve good results, which verify the effectiveness of the shape descriptor. The highest recognition rate is 88.83% for SVM and 87.38% for ANN, which means that the performance of the SVM is better than that of the ANN.

3D depth image analysis for indoor fall detection of elderly people

This paper presents a new fall detection method of etderly people in a room environment based on shape analysis of 3D depth images captured by a Kinect sensor. Depth images are pre- processed by a median filter both for background and target. The sithouette of moving individual in depth images is achieved by a subtraction method for background frames. The depth images are converted to disparity map, which is obtained by the horizontal and vertical projection histogram statistics. The initial floor plane information is obtained by V disparity map, and the floor ptane equation is estimated by the least square method. Shape information of human subject in depth images is analyzed by a set of moment functions. Coefficients of ellipses are calculated to determine the direction of individual The centroids of the human body are catculated and the angle between the human body and the floor plane is calculated. When both the distance from the centroids of the human body to the floor plane and the angle between the human body and the floor plane are tower than some threshotds, fall incident will be detected. Experiments with different failing direction are performed. Experimental results show that the proposed method can detect fall incidents effectively.

A flower image retrieval method based on ROI feature

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

Recognition of Greenhouse Cucumber Disease Based on Image Processing Technology

This paper mainly studies the disease of cucumber downy mildew, powdery mildew and anthracnose leaf image processing and recognition technologies. Application of median filtering method of filtering noise, leaf spot disease of cucumber leaf color range segmentation part extract color feature parameters of the lesion site, characteristic parameters of the shape;extraction texture parameters by using gray level co-occurrence matrix. Based on the shortest distance methods to identify diseases of images. The experimental result showed that the current method on disease recognition accuracy rates more than 96%.