Design and Implementation of the Image Interactive System Based on Human-Computer Interaction

Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide users more experience. In the article, a new way of detecting moving things is given on the basis of development of the image processing technique. The system architecture decides that the communication should be used between two different applications. After considered, named pipe is selected from many ways of communication to make sure that video is keeping in step with the movement from the analysis of the people moving. According to a large amount of data and principal knowledge, thinking of the need of actual project, a detailed system design and realization is finished. The system consists of three important modules: detecting of the people's movement, information transition between applications and video showing in step with people's movement. The article introduces the idea of each module and technique.

Interactive Image Enhancement by Fuzzy Relaxation

In this paper, an interactive image enhancement （HE） technique based on fuzzy relaxation is presented, which allows the user to select different intensity levels for enhancement and intermit the enhancement process according to his/her preference in applications. First, based on an analysis of the convergence of a fuzzy relaxation algorithm for image contrast enhancement, an improved version of this algorithm, which is called FuzzIIE Method 1, is suggested by deriving a relationship between the convergence regions and the parameters in the transformations defined in the algorithm. Then a method called FuzzIIE Method 2 is introduced by using a different fuzzy relaxation function, in which there is no need to re-select the parameter values for interactive image enhancement. Experimental results are presented demonstrating the enhancement capabilities of the proposed methods under different conditions.

Fast interactive segmentation algorithm of image sequences based on relative fuzzy connectedness

A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex hackground and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.

Exploiting Human Pose and Scene Information for Interaction Detection

Identifying human actions and interactions finds its use in manyareas, such as security, surveillance, assisted living, patient monitoring, rehabilitation,sports, and e-learning. This wide range of applications has attractedmany researchers to this field. Inspired by the existing recognition systems,this paper proposes a new and efficient human-object interaction recognition(HOIR) model which is based on modeling human pose and scene featureinformation. There are different aspects involved in an interaction, includingthe humans, the objects, the various body parts of the human, and the backgroundscene. Themain objectives of this research include critically examiningthe importance of all these elements in determining the interaction, estimatinghuman pose through image foresting transform (IFT), and detecting the performedinteractions based on an optimizedmulti-feature vector. The proposedmethodology has six main phases. The first phase involves preprocessing theimages. During preprocessing stages, the videos are converted into imageframes. Then their contrast is adjusted, and noise is removed. In the secondphase, the human-object pair is detected and extracted from each image frame.The third phase involves the identification of key body parts of the detectedhumans using IFT. The fourth phase relates to three different kinds of featureextraction techniques. Then these features are combined and optimized duringthe fifth phase. The optimized vector is used to classify the interactions in thelast phase. TheMSRDaily Activity 3D dataset has been used to test this modeland to prove its efficiency. The proposed system obtains an average accuracyof 91.7% on this dataset.

MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.

Influence of the interaction volume on the kinetic energy resolution of a velocity map imaging spectrometer

We investigate the influence of the interaction volume on the energy resolution of a velocity map imaging spectrometer. The simulation results show that the axial interaction size has a significant influence on the resolution. This influence is increased for a higher kinetic energy. We further show that the radial interaction size has a minor influence on the energy resolution for the electron or ion with medium energy, but it is crucial for the resolution of the electron or ion With low kinetic energy. By tracing the flight trajectories we show how the electron or ion energy resolution is influenced by the interaction size.

Interaction between Bax and Bcl-XL proteins confirmed by partial acceptor photobleaching-based FRET imaging

Exact interaction mechanism between Bax and Bcl-XL,two key Bcl-2 family proteins,is an interesting and controversial issue.Partial acceptor photobleaching-based quantitative fluores-cence resonance energy transfer(FRET)measurement,PbFRET,is a widely used FRET quantification method in living cells.In this report,we implemented pixel-to-pixel PbFRET imaging on a wide-field microscope to map the FRET efficiency(E)images of single living HepG2 cells co-expressing CFP-Bax and YFP-Bcl-XL.The E value between CFP-Bax and YFP-Bcl-XL was 4.59%in cytosol and 11.31%on mitochondria,conclusively indicating the direct interaction of the two proteins,and the interaction of the two proteins was strong on mitochondria and modest in cytosol.

Imaging performance evaluation in depth-of-interaction PET with a new method of sinogram generation:A Monte Carlo simulation study

In conventional PET systems,the parallax error degrades image resolution and causes image distortion.To remedy this,a PET ring diameter has to be much larger than the required size of field of view(FOV),and therefore the cost goes up.Measurement of depth-of-interaction(DOI)information is effective to reduce the parallax error and improve the image quality.This study is aimed at developing a practical method to incorporate DOI information in PET sinogram generation and image reconstruction processes and evaluate its efficacy through Monte Carlo simulation.An animal PET system with 30-mm long LSO crystals and 2-mm DOI measurement accuracy was simulated and list-mode PET data were collected.A sinogram generation method was proposed to bin each coincidence event to the correct LOR location according to both incident crystal indices and DOI positions of the two annihilation photons.The sinograms were reconstructed with an iterative OSMAPEM(ordered subset maximum a posteriori expectation maximization)algorithm.Two phantoms(a rod source phantom and a Derenzo phantom)were simulated,and the benefits of DOI were investigated in terms of reconstructed source diameter(FWHM)and source positioning accuracy.The results demonstrate that the proposed method works well to incorporate DOI information in data processing,which not only overcomes the image distortion problem but also significantly improves image resolution and resolution uniformity and results in satisfactory image quality.

An algorithm supporting fast scheduling and viewing of remote sensing images in embedded devices

In order to resolve the conflict between the limited resources of embedded devices and the growing amount of massive image data to be shown, a solution for fast images rendering in embedded devices is proposed and implemented. First, an improved algorithm of a multi-resolution file-pyramid construction which is used for the organization of massive image data is presented. Then, a strategy, adopting technologies such as view-dependent levels of detail, target-tiles quick search and tiles seamless connection, is presented for fast scheduling and viewing of images. The results show that compared with the solution of multi-scale image representations based on wavelet, the proposed solution can improve the rendering speed, and the rendering speed does not depend on the image size, though it increases some data storage space. And the proposed solution is suitable for embedded devices and friendly experience.

Stereo particle image velocimetry measurement of 3D soil deformation around laterally loaded pile in sand

A developed stereo particle image velocimetry(stereo-PIV) system was proposed to measure three-dimensional(3D) soil deformation around a laterally loaded pile in sand.The stereo-PIV technique extended 2D measurement to 3D based on a binocular vision model,where two cameras with a well geometrical setting were utilized to image the same object simultaneously.This system utilized two open software packages and some simple programs in MATLAB,which can easily be adjusted to meet user needs at a low cost.The failure planes form an angle with the horizontal line,which are measured at 27°-29°,approximately three-fourths of the frictional angle of soil.The edge of the strain wedge formed in front of the pile is an arc,which is slightly different from the straight line reported in the literature.The active and passive influence zones are about twice and six times of the diameter of the pile,respectively.The test demonstrates the good performance and feasibility of this stereo-PIV system for more advanced geotechnical testing.

Experimental and numerical investigation on sound generation from airfoil-flow interaction

Aerodynamic noise due to interaction between incoming turbulence and rotating blades is an important component in the wind turbine noise. The rod-airfoil configuration is used to investigate the interactive phenomenon experimentally and nu- merically. Distribution of unsteady pressure on the airfoil surface is measured for different rod positions and airfoil attack angles. Two National Advisory Committee for Aeronatics （NACA） airfoils, NACA0012 and NACA0018, and two wind turbine airfoils, S809 and S825 are investigated. In addition, for low angles of attack, the flow field around the airfoil＇s leading edge is investigated with the particle image velocimetry （PIV）. The experimental results indicate that unsteady pressure disturbances on the airfoil surface are related to the rod vortex shedding. Meanwhile, the interaction flow field of the rod and NACA0012 airfoil is simulated with the unsteady Reynolds averaged Navier-Stokes method （URANS）, and the obtained pressure spectra are compared with the experimental results.

On the Wake Flow Interaction between Model Turbines with Varying Streamwise Distance

Wind tunnel measurements using particle image velocimetry have been performed around two perforated discs, with varying streamwise distance, in order to simulate the wake interaction between wind turbines. The static pressure footprint (p-f) on ground level associated with the wake behind the disc and wake velocity data for both the streamwise and wall-normal velocity components with the corresponding turbulence intensities are reported. The p-f method shows that the size of the wake regions, behind the wind turbine models, initially drop when a second disc is placed just downstream of the first one. From a mutual distance (Δ χ) of about five disc diameters (5D), both wake footprints increase as the mutual distance is increased, and for very large mutual distances, approximately Δ χ/ D > 15, the footprint of the downstream disc has recovered and is about the same as for a single disc. At last we conclude that despite very different inlet conditions to the discs, with about 50% of reduced velocity on the centre line upstream of the second disc and an increase of the maximum streamwise fluctuations by 90%, the mean velocities in the wake are proven to scale with the hub height velocity.

Research on Teaching Method of Children’s Image Cognition Based on AR Technology

In this paper,the research on the teaching method of children’s image cognition based on AR technology is carried out.By analyzing the principle ofARtechnology to recognize images,we understand thatARtechnology can promote children’s image cognition,and this teaching method is in line with the Tower of Experience theory.It further analyzes the current situation of children’s image cognition teaching with simple teaching methods,backward AR teaching tools,and poor perception of teaching objects.Teachers’traditional image teaching methods cannot effectively and efficiently improve children’s image cognition.Therefore,based on AR technology,two commonly used image cognition teaching methods are proposed:AR interactive picture book education andARinteractive game education.Both of these educational methods can improve children’s ability to recognize images.

Visualization of Three-dimensional Human Data Based on CT Image

Three-dimensional medical image visualization becomes an essential part for medical field, including computer aided diagnosis, surgery planning and simulation, artificial limb surgery, radiotherapy planning, and teaching etc. In this paper, marching cubes algorithm is adopted to reconstruct the 3-D images for the CT image sequence in DICOM format under theVC＋＋6.0 and the visual package VTK platform. The relatively simple interactive operations such as rotation and transfer can be realized on the platform. Moreover, the normal vector and interior point are calculated to form the virtual clipping plane, which is then used to incise the 3-D object. Information of the virtual slice can be obtained, in the mean while the virtual slice images are displayed on the screen. The technique can realize the real time interaction extraction of virtual slice on 3-D CT image. The cuboids structured can be zoomed, moved and eircumrotated by operating mouse to incise the 3-D reconstruction object. Real time interaction can be realized by clipping the reconstruction object. The coordinates can be acquired by the mouse clicking in the 3D space, to realize the point mouse pick-up as well angle and distance interactive measurement. We can get quantitative information about 3-D images through measurement.

网红经济时代旅游地意象塑造演化的过程机制研究——以“淄博烧烤”为例

聚焦网红旅游地淄博,参照网络文本分析法,探究旅游地和游客多主体间互动推动旅游地意象持续塑造演化过程机制。结果显示:(1)网红经济时代“淄博烧烤”意象是在旅游地和游客互动耦合下被塑造并不断叠加演化;(2)意象演化经历了网络发酵期、政府主导期、游客自发期和意象回稳期,各阶段意象驱动力分别是网络媒介、政府主体、游客行为和稳固意象,且演化过程类似旅游地生命周期理论,但因网红经济特性,其生命周期时长及演化速度有所不同;(3)居民以积极参与和热情态度一改“主客”不平衡关系,勾勒出良好意象的清晰事实,凸显其在意象塑造中的地位和作用。

文化符号的传播与共享——以夏鲁寺、贡嘎曲德寺日月图像为例

西藏地区的夏鲁寺与贡嘎曲德寺壁画中均出现了以金乌、玉兔代表日与月的图像。金乌与玉兔图像是中原文化用来表示日与月的固定图式。自汉朝时期由西王母神话与民间信仰不断糅合产生,唐代时被吸收进佛教图像体系中,后期随着藏传佛教的兴盛与文化交流的频繁,藏传佛教绘画吸收了这种日月图像母题。西藏壁画艺术中的日月图像,不仅更新了藏传佛教艺术的表达范式,而且图像意义也突破了单纯宗教艺术的阐释,凸显了中央皇权的在场。夏鲁寺与贡嘎曲德寺壁画中的日月图像是汉藏文化交往交流交融的结果,彰显了元明时期各民族之间的频繁互动,以及多元文化交流下文化符号互融互生的整体性社会结构。

局部注意力引导下的全局池化残差分类网络

大部分注意力机制虽然能增强图像特征,但没有考虑局部特征的关联性影响特征整体的问题。针对以上问题,本文提出局部注意力引导下的全局池化残差分类网络(MSLENet)。MSLENet的基线网络为ResNet34,首先改变首层结构,保留图像重要信息;其次提出多分割局部增强注意力机制(MSLE)模块,MSLE模块将图像整体分割成多个小图像,增强每个小图像的局部特征,通过特征组交互的方式将局部重要特征引导到全局特征中;最后提出池化残差(PR)模块来处理ResNet残差结构丢失信息的问题,提高各层之间的信息利用率。实验结果表明,MSLENet通过增强局部特征的关联性,在多个数据集上均有良好的效果,有效地提高了网络的表达能力。

基于结构功能交叉神经网络的多模态医学图像融合

针对多模态医学图像融合中存在纹理细节模糊和对比度低的问题,提出了一种结构功能交叉神经网络的多模态医学图像融合方法。首先,根据医学图像的结构信息和功能信息设计了结构功能交叉神经网络模型,不仅有效地提取解剖学和功能学医学图像的结构信息和功能信息,而且能够实现这两种信息之间的交互,从而很好地提取医学图像的纹理细节信息。其次,利用交叉网络通道和空间特征变化构造了一种新的注意力机制,通过不断调整结构信息和功能信息权重来融合图像,提高了融合图像的对比度和轮廓信息。最后,设计了一个从融合图像到源图像的分解过程,由于分解图像的质量直接取决于融合结果,因此分解过程可以使融合图像包含更多的细节信息。通过与近年来提出的7种高水平方法相比,本文方法的AG,EN,SF,MI,QAB/F和CC客观评价指标分别平均提高了22.87%,19.64%,23.02%,12.70%,6.79%,30.35%,说明本文方法能够获得纹理细节更清晰、对比度更好的融合结果,在主观视觉和客观指标上都优于其他对比算法。

改进YOLOv4的遥感图像目标检测算法

为有效解决遥感图像目标检测算法在复杂背景下的检测效果不佳的问题,提出一种改进YOLOv4的目标检测算法。设计一种跨阶段残差结构,替换原主干网络的简单残差结构,降低模型参数量和计算负担;引入CBAM注意力机制,加强CSP模块间有效特征交互;使用跨阶段分层卷积模块重构特征融合阶段对深层特征图的处理方式,防止网络退化和梯度消失;采用Mish激活函数,增强融合网络对非线性特征的提取能力。在RSOD、DIOR数据集上的实验结果表明,改进YOLOv4算法的测试mAP相比原YOLOv4算法分别高出4.5%、7.3%,其检测速度分别达到48 fps、45 fps,在保证实时性的同时检测精度有较大提升。

混合注意力与多特征交互的去雾算法

为解决目前深度学习去雾算法在处理非均匀雾天图像时无法有效利用多尺度特征,导致复原出的图像产生颜色失真、细节恢复不完整等问题,提出了混合注意力与多特征交互的图像去雾算法。首先,利用编码模块提取不同尺度的特征;其次,构造混合注意力模块,从全局角度对图像雾气进行感知,并利用通道注意力机制对不同雾浓度分配权重;然后,设计多特征交互模块,实现不同尺度特征间的信息交换,有效利用低分辨率特征中的语义信息,同时保留了高分辨率特征的空间细节与颜色信息,并利用门控融合模块聚合不同尺度的特征;最后,解码模块对融合后的特征进行重构,得到无雾图像。实验结果表明,运用本文提出的算法恢复的去雾图像不仅主观上颜色自然、细节清晰,而且在客观指标上也优于现有的主流算法。该研究结果可为深度学习去雾研究与应用提供新的方案。