New templates of CNN for extracting corners of objects in gray-scale images

A new cellular neural network (CNN) with nonlinear templates is presented forextracting convex corners of objects in gray-scale images. Application examples showed that the newCNN can even detect convex corner characteristics of objects in images with Gaussian noise.

AN ADAPTIVE DIGITAL IMAGE WATERMARK ALGORITHM BASED ON GRAY-SCALE MORPHOLOGY

An adaptive digital image watermark algorithm with strong robustness based on gray-scale morphology is proposed in this paper.The embedded strategies include:The algorithm seeks and extracts adaptively the image strong texture regions.The algorithm maps the image strong texture region to the wavelet tree structures, and embeds adaptively watermark into the wavelet coefficients corresponding to the image's strong texture regions.According to the visual masking features, the algorithm adjusts adaptively the watermark-embedding intensity.Experimental results show the algorithm is robust to compression, filtering, noise as well as strong shear attacks.The algorithm is blind watermark scheme.The image strong texture region extraction method based on morphology in this algorithm is simple and effective and adaptive to various images.

Iterative static modeling of channelized reservoirs using history-matched facies probability data and rejection of training image

Most inverse reservoir modeling techniques require many forward simulations, and the posterior models cannot preserve geological features of prior models. This study proposes an iterative static modeling approach that utilizes dynamic data for rejecting an unsuitable training image(TI) among a set of TI candidates and for synthesizing history-matched pseudo-soft data. The proposed method is applied to two cases of channelized reservoirs, which have uncertainty in channel geometry such as direction, amplitude, and width. Distance-based clustering is applied to the initial models in total to select the qualified models efficiently. The mean of the qualified models is employed as a history-matched facies probability map in the next iteration of static models. Also, the most plausible TI is determined among TI candidates by rejecting other TIs during the iteration. The posterior models of the proposed method outperform updated models of ensemble Kalman filter(EnKF) and ensemble smoother(ES) because they describe the true facies connectivity with bimodal distribution and predict oil and water production with a reasonable range of uncertainty. In terms of simulation time, it requires 30 times of forward simulation in history matching, while the EnKF and ES need 9000 times and 200 times, respectively.

Static-shift suppression and anti-interference signal processing for CSAMT based on Guided Image Filtering

Shallow conductive heterogeneity can lead to static shifts ain the apparent resistivity sounding curve of controlled-source audio-frequency magnetotellurics(CSAMT).The static effect will shift the apparent resistivity curves along with axial log-log coordinates.Such an effect,if not properly processed,can distort the resistivity of rock formation and the depth of interfaces,and even make the geological structures unrecognizable.In this paper,we discuss the reasons and characteristics of the static shift and summarize the previous studies regarding static shift correction.Then,we propose the Guided Image Filtering algorithm to suppress static shifts in CSAMT.In detail,we use the multi-window superposition method to superimpose 1D signals into a 2D matrix image,which is subsequently processed with Guided Image Filtering.In the synthetic model study and field examples,the Guided Image Filtering algorithm has effectively corrected and suppressed static shifts,and finally improved the precision of data interpretation.

A Fast Underwater Optical Image Segmentation Algorithm Based on a Histogram Weighted Fuzzy C-means Improved by PSO

The S/N of an underwater image is low and has a fuzzy edge.If using traditional methods to process it directly,the result is not satisfying.Though the traditional fuzzy C-means algorithm can sometimes divide the image into object and background,its time-consuming computation is often an obstacle.The mission of the vision system of an autonomous underwater vehicle (AUV) is to rapidly and exactly deal with the information about the object in a complex environment for the AUV to use the obtained result to execute the next task.So,by using the statistical characteristics of the gray image histogram,a fast and effective fuzzy C-means underwater image segmentation algorithm was presented.With the weighted histogram modifying the fuzzy membership,the above algorithm can not only cut down on a large amount of data processing and storage during the computation process compared with the traditional algorithm,so as to speed up the efficiency of the segmentation,but also improve the quality of underwater image segmentation.Finally,particle swarm optimization (PSO) described by the sine function was introduced to the algorithm mentioned above.It made up for the shortcomings that the FCM algorithm can not get the global optimal solution.Thus,on the one hand,it considers the global impact and achieves the local optimal solution,and on the other hand,further greatly increases the computing speed.Experimental results indicate that the novel algorithm can reach a better segmentation quality and the processing time of each image is reduced.They enhance efficiency and satisfy the requirements of a highly effective,real-time AUV.

A Target-Orientated Marker Image Binarization Method for Orthopaedic Surgical Navigation System

Camera calibration is the key technique in a C-arm based orthopaedic surgical navigation system. The extraction of marker location information is a necessary step in the calibration process. Ideal marker images should possess uniform background and contain marker shadow only, but in fact marker images always possess nonuniform background and are contaminated by noise and unwanted anatomic information, making the extraction very difficult. A target-orientated marker shadow extraction method was proposed. With this method a proper threshold for marker image binarization can be determined.

High-resolution Remote Sensing Image Segmentation Using Minimum Spanning Tree Tessellation and RHMRF-FCM Algorithm

It is proposed a high resolution remote sensing image segmentation method which combines static minimum spanning tree(MST)tessellation considering shape information and the RHMRF-FCM algorithm.It solves the problems in the traditional pixel-based HMRF-FCM algorithm in which poor noise resistance and low precision segmentation in a complex boundary exist.By using the MST model and shape information,the object boundary and geometrical noise can be expressed and reduced respectively.Firstly,the static MST tessellation is employed for dividing the image domain into some sub-regions corresponding to the components of homogeneous regions needed to be segmented.Secondly,based on the tessellation results,the RHMRF model is built,and regulation terms considering the KL information and the information entropy are introduced into the FCM objective function.Finally,the partial differential method and Lagrange function are employed to calculate the parameters of the fuzzy objective function for obtaining the global optimal segmentation results.To verify the robustness and effectiveness of the proposed algorithm,the experiments are carried out with WorldView-3(WV-3)high resolution image.The results from proposed method with different parameters and comparing methods(multi-resolution method and watershed segmentation method in eCognition software)are analyzed qualitatively and quantitatively.

Effects of gradient high-field static magnetic fields on diabetic mice

Although 9.4 T magnetic resonance imaging(MRI) has been tested in healthy volunteers,its safety in diabetic patients is unclear.Furthermore,the effects of high static magnetic fields(SMFs),especially gradient vs.uniform fields,have not been investigated in diabetics.Here,we investigated the consequences of exposure to 1.0-9.4 T high SMFs of different gradients(>10 T/m vs.0-10 T/m)on type 1 diabetic(T1D) and type 2 diabetic(T2D) mice.We found that 14 h of prolonged treatment of gradient(as high as 55.5 T/m) high SMFs(1.0-8.6 T) had negative effects on T1D and T2D mice,including spleen,hepatic,and renal tissue impairment and elevated glycosylated serum protein,blood glucose,inflammation,and anxiety,while 9.4 T quasi-uniform SMFs at 0-10 T/m did not induce the same effects.In regular T1D mice(blood glucose>16.7 mmol/L),the>10 T/m gradient high SMFs increased malondialdehyde(P<0.01) and decreased superoxide dismutase(P<0.05).However,in the severe T1D mice(blood glucose≥30.0 mmol/L),the>10 T/m gradient high SMFs significantly increased tissue damage and reduced survival rate.In vitro cellular studies showed that gradient high SMFs increased cellular reactive oxygen species and apoptosis and reduced MS-1 cell number and proliferation.Therefore,this study showed that prolonged exposure to high-field(1.0-8.6 T)>10 T/m gradient SMFs(35-1 380 times higher than that of current clinical MRI)can have negative effects on diabetic mice,especially mice with severe T1D,whereas 9.4 T high SMFs at 0-10T/m did not produce the same effects,providing important information for the future development and clinical application of SMFs,especially high-field MRI.

Development of a Drape-Tester by Image Analysis

An instrument is developed to measure the dynamic andstatic fabric drapability by the technology of image analy-sis. A set of stepper motor speed - regulation system,which is based on the control of single - chip microproces-sor and microcomputer, is developed to form the dynamictest environment in order to implement the measurementof dynamic drapability. An algorithm is presented to con-vert the original draped images which are captured by adigital camera into binary images. The test results showthat the algorithm is adapted for all kinds of fabrics. Thewhole measurement process is controlled by a

A New Method Which Combines Arithmetic Coding with RLE for Lossless Image Compression

This paper presents a new method of lossless image compression. An image is characterized by homogeneous parts. The bit planes, which are of high weight are characterized by sequences of 0 and 1 are successive encoded with RLE, whereas the other bit planes are encoded by the arithmetic coding (AC) (static or adaptive model). By combining an AC (adaptive or static) with the RLE, a high degree of adaptation and compression efficiency is achieved. The proposed method is compared to both static and adaptive model. Experimental results, based on a set of 12 gray-level images, demonstrate that the proposed scheme gives mean compression ratio that are higher those compared to the conventional arithmetic encoders.

An Alternate Approach for Designing a Domain Specific Image Search Prototype Using Histogram

Everyone knows that thousand of words are represented by a single image. As a result, image search has become a very popular mechanism for the Web-searchers. Image search means, the search results are produced by the search engine should be a set of images along with their Web-page Unified Resource Locator (URL). Now Web-searcher can perform two types of image search, they are “Text to Image” and “Image to Image” search. In “Text to Image” search, search query should be a text. Based on the input text data, system will generate a set of images along with their Web-page URL as an output. On the other hand, in “Image to Image” search, search query should be an image and based on this image, system will generate a set of images along with their Web-page URL as an output. According to the current scenarios, “Text to Image” search mechanism always not returns perfect result. It matches the text data and then displays the corresponding images as an output, which is not always perfect. To resolve this problem, Web researchers have introduced the “Image to Image” search mechanism. In this paper, we have also proposed an alternate approach of “Image to Image” search mechanism using Histogram.

山地地震勘探中的静校正对成像质量的影响及改进策略

在山地地震勘探中,地震数据常常被校正到固定基准面上进行偏移成像,从而造成成像失真。本文从数学上直接推导公式,证明了静校正后从基准面进行偏移会造成倾角误差;通过山地起伏地表正演模型,说明了静校正后从基准面偏移会扭曲波场,导致严重的偏移成像失真。此外,应用四川南部山区的实际案例,分别从基准面偏移及从起伏地表偏移,叠前时间偏移和深度偏移结果均表明,在复杂的山地地形中,剧烈的高差变化会导致固定基准面偏移成像失真,应用起伏地表偏移能改进山地地震勘探资料的成像质量。本文的研究结果对理论研究和实际地震数据处理具有重要意义。

一种大孔径静态干涉高光谱成像数据压缩方法

大孔径静态干涉成像遥感数据的数据量较大,需要寻找一种合适的方法对其压缩。从大孔径静态干涉成像机理出发,分析了干涉数据的空间和干涉维冗余性,并基于现有成熟混合压缩编码方法,提出了基于相似干涉曲线与不同光程差之间冗余去除的算法,对冗余数据进行去除预处理。对干涉数据进行基于曲线表的干涉曲线编码表示,对不同光程差之间的图像进行相关性预测,减少了大孔径静态干涉成像遥感图像的量化深度并降低了图像的信息熵,再结合JPEG2000算法进行无损或有损压缩。实验结果表明,对于大孔径静态干涉成像数据,该算法可实现压缩比为3.1倍的无损压缩,有损压缩的率失真曲线也优于其他对比算法,其复原图像反演出的光谱曲线的光谱角和相对二次误差均优于其他对比算法处理的数据,有效保护了光谱信息。

不同一次性拉伸方式对腘绳肌形态的急性影响

研究一次性静态拉伸与一次性动态拉伸对双关节腘绳肌组织形态的急性影响。方法:采集10名无腘绳肌损伤成年男性在一次性静态拉伸与一次性动态拉伸前后腘绳肌肌腹的全景超声图像,比较不同拉伸方式前后股二头肌长头(BFLH)、半膜肌(SM)与半腱肌(ST)的组织形态变化。结果:一次性动态拉伸与一次性静态拉伸均可延长BFLH、SM与ST的肌束长度(P<0.01),但均不改变肌肉厚度(P>0.05)。在两种拉伸前后,肌束长度与肌肉厚度均存在BFLH、SM与ST之间的差异(P<0.01),其中肌束长度由大到小依次为ST、BFLH、SM,肌肉厚度由大到小依次为SM、BFLH、ST。一次性动态拉伸作用下,BFLH的肌束延长率大于ST的肌束延长率(P<0.01),BFLH和ST肌束延长率均与SM无差异。一次性静态拉伸作用下,SM的肌束延长率大于ST(P<0.05),SM和ST肌束延长率均与BFLH无差异。相比于一次性动态拉伸,一次性静态拉伸使BFLH肌束延长率更低(P<0.01),SM与ST肌束延长率均不存在拉伸方式间的差异。结论:相比一次性静态拉伸,一次性动态拉伸可更明显地改变BFLH形态。ST与SM的形态均可被两种拉伸方式改变,但二者形态变化程度均无拉伸方式间的差别。三条腘绳肌之间存在结构差异,且在拉伸作用下发生了不同程度的形态变化。研究结果可为拉伸类型选择及后续研究提供理论依据。

室内机器人动态SLAM技术

随着计算机视觉、深度学习的发展,基于视觉的静态SLAM研究不断改进,然而大多数SLAM算法存在静态假定不成立和累计漂移。针对上述问题,设计动态BN-SLAM算法,利用深度图像的几何信息对原始掩模进行修正,修正掩膜用于移除运动物体及其影响。设计加权RANSAC方法,求解摄像机局部位姿。在TUM数据集上的实验结果表明,BN-SLAM的ATE、平移RPE和旋转RPE的平均RMSE值分别为95.46%、92.45%和90.88%,平均S.D.值分别为94.88%、94.76%和92.80%,跟踪轨迹点结果的平均率为98.80%。在真实环境的实验结果表明,BN-SLAM能够剔除运动的人造成的地图污染。

基于静息态功能磁共振成像探讨卒中后疲劳的中枢机制

目的应用静息态功能磁共振成像探讨卒中后疲劳(post-stroke fatigue,PSF)的中枢机制。方法随机选取2019年4月至2021年9月就诊于河北医科大学第二医院的急性脑梗死患者,分别在脑梗死急性期(发病14天内)和慢性期(发病3个月后)对被试者进行疲劳严重程度量表评估及功能磁共振成像检查,根据疲劳程度分组,应用MATLAB R2013b软件对数据进行处理,分析两组间小世界属性特征值γ、λ、σ、Cp、Lp和全脑静态功能网络连接(static functional network connectivity,sFNC)的差异,并将差异脑区与临床资料进行相关性分析。结果脑梗死急性期和慢性期两组性别、年龄差异均无统计学意义(P>0.05);两组脑网络均具有小世界属性(σ>1,γ>1,λ≈1),其中慢性期PSF组λ和Cp的曲线下面积较NPSF组减小,差异均有统计学意义(P<0.05),其余特征性参数曲线下面积差异均无统计学意义(P>0.05);梗死急性期PSF组与NPSF组相比,左侧额顶网络与视觉网络(visual network,VN)等多个网络的sFNC减低(P<0.05),双侧额顶网络分别与默认模式网络及感觉运动网络间的sFNC增高(P<0.05)。慢性期,与NPSF组相比,PSF组右侧额顶网络VN的sFNC减低(P<0.05),认知网络如默认模式网络与其他多个网络间sFNC增高(P<0.05)。结论脑梗死急性期PSF的发生可能与认知功能异常相关;脑梗死慢性期PSF患者部分脑网络间sFNC增强可能导致认知功能障碍,推测RFPN-VN的sFNC减低是高级执行网络功能过强而产生的抑制性代偿作用。

Understanding and Detecting Inefficient Image Displaying Issues in Android Apps

Mobile applications(apps for short)often need to display images.However,inefficient image displaying(IID)issues are pervasive in mobile apps,and can severely impact app performance and user experience.This paper first establishes a descriptive framework for the image displaying procedures of IID issues.Based on the descriptive framework,we conduct an empirical study of 216 real-world IID issues collected from 243 popular open-source Android apps to validate the presence and severity of IID issues,and then shed light on these issues’characteristics to support research on effective issue detection.With the findings of this study,we propose a static IID issue detection tool TAPIR and evaluate it with 243 real-world Android apps.Encouragingly,49 and 64 previously-unknown IID issues in two different versions of 16 apps reported by TAPIR are manually confirmed as true positives,respectively,and 16 previously-unknown IID issues reported by TAPIR have been confirmed by developers and 13 have been fixed.Then,we further evaluate the performance impact of these detected IID issues and the performance improvement if they are fixed.The results demonstrate that the IID issues detected by TAPIR indeed cause significant performance degradation,which further show the effectiveness and efficiency of TAPIR.

高原冻土地表地震勘探技术及应用

青藏高原是国家的能源战略后备区之一,油气资源储藏丰富,但表层冻土发育,地震波场复杂,油气地震勘探面临诸多挑战。针对青藏高原冻土地表特点,一是采用“低频可控震源激发、高密度宽线观测、长排列+小组合接收”技术,克服冻土对中深层的反射能量屏蔽和噪音干扰,降低地震工程作业对环境的影响;二是通过低信噪比初至处理技术、高精度约束层析反演技术、空变多域初至波剩余静校正技术提高冻土地表初至拾取精度和层析反演模型精度,解决冻土表层速度剧烈变化带来的静校正问题;三是采用基于冻土层有效反射频带的去噪技术、基于AMT反演约束的冻土层速度拾取技术、基于分偏移距叠加成像的精细切除技术,有效去除冻土地表噪音影响,指导速度拾取和精细切除。上述技术可以获得高品质的地震资料,为油气及矿产资源等地震勘探奠定坚实的基础。

基于红外成像原理的防静电面料中导电纤维分布的快速测定技术研究

防静电织物可有效减少服装上的静电积聚,减少安全隐患,已经在航空航天、汽车、电子等领域得到广泛应用,对国防军工和国民经济发展具有重大意义。文章阐述了一种基于红外成像原理的防静电面料中导电材料分布的快速测定技术的开发过程,结果表明,当电压为140 V、电极距离为3 cm时,所呈现的图像最为清晰,能较为准确快速地判定防静电织物中导电纤维分布位置和规律,有利于提升产品质量,提高个体防护能力。

T800复合材料层压板损伤引入技术研究

本文针对国产T800级碳纤维增强复合材料开展多次低速冲击损伤与准静态压痕损伤及最终剩余强度对比研究,以提出一种高效的复合材料损伤引入方式。首先开展多次冲击及静压痕损伤引入试验,在达到目标凹坑深度时,通过目视观测及超声C扫分析不同损伤引入方式产生损伤的机理及损伤模式;其次,对达到目标凹坑深度的试验件进行压缩剩余强度测试,分析不同损伤引入方式、不同凹坑深度、不同损伤面积与剩余强度之间的关系;通过DIC(Digital Image Correlation)、声发射系统监测对剩余强度试验过程进行监测,确定不同损伤引入方式的试验件在压缩中的损伤演化过程及机理。通过以上研究,最终确定一种高效的损伤引入方式。