A self-adapting image encryption algorithm based on spatiotemporal chaos and ergodic matrix

To ensure the security of a digital image, a new self-adapting encryption algorithm based on the spatiotemporal chaos and ergodic matrix is proposed in this paper. First, the plain-image is divided into different blocks of the same size, and each block is sorted in ascending order to obtain the corresponding standard ergodic matrix. Then each block is encrypted by the spatiotemporal chaotic system and shuffled according to the standard ergodic matrix. Finally, all modules are rearranged to acquire the final encrypted image. In particular, the plain-image information is used in the initial conditions of the spatiotemporal chaos and the ergodic matrices, so different plain-images will be encrypted to obtain different cipherimages. Theoretical analysis and simulation results indicate that the performance and security of the proposed encryption scheme can encrypt the image effectively and resist various typical attacks.

Improving effect of carbonized quantum dots(CQDs)in pure copper matrix composites

Carbon quantum dots(CQDs),which contain a core structure composed of sp^(2)carbon,can be used as the reinforcing phase like graphene and carbon nanotubes in metal matrix.In this paper,the CQD/Cu composite material was prepared by powder metallurgy method.The composite powder was prepared by molecular blending method and ball milling method at first,and then densified into bulk material by spark plasma sintering(SPS).X-ray diffraction,Raman spectroscopy,infrared spectroscopy,and nuclear magnetic resonance were employed to characterize the CQD synthesized under different temperature conditions,and then CQDs with a higher degree of sp^(2)were utilized as the reinforcement to prepare composite materials with different contents.Mechanical properties and electrical conductivity results show that the tensile strength of the 0.2 CQD/Cu composite material is~31%higher than that of the pure copper sample,and the conductivity of 0.4 CQD/Cu is~96%IACS,which is as high as pure copper.TEM and HRTEM results show that good interface bonding of CQD and copper grain is the key to maintaining high mechanical and electrical conductivity.This research provides an important foundation and direction for new carbon materials reinforced metal matrix composites.

An algorithm for segmentation of lung ROI by mean-shift clustering combined with multi-scale HESSIAN matrix dot filtering

A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original image was firstly filtered by multi-scale HESSIAN matrix dot filters,round suspected nodular lesions in the image were enhanced,and linear shape regions of the trachea and vascular were suppressed.Then,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature space.The kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature information.Finally,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering segmentation.Experimental results show that by the introduction of HESSIAN matrix of dot filtering information to mean-shift clustering,nodular regions can be segmented from blood vessels,trachea,or cross regions connected to the nodule,non-nodular areas can be removed from ROIs properly,and ground glass object(GGO)nodular areas can also be segmented.For the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.

HESSIAN MATRIX BASED SADDLE POINT DETECTION FOR GRANULES SEGMENTATION IN 2D IMAGE

Segmenting the touching objects in an image has been remaining as a hot subject due to the problematic complexities, and a vast number of algorithms designed to tackle this issue have come into being since a decade ago. In this paper, a new granule segmentation algorithm is developed using saddle point as the cutting point. The image is binarized and then sequentially eroded to form a gray-scale topographic counterpart, followed by using Hessian matrix computation to search for the saddle point. The segmentation is performed by cutting through the saddle point and along the maximal gradient path on the topographic surface. The results of the algorithm test on the given real images indicate certain superiorities in both the segmenting robustness and execution time to the referenced methods.

Total Variation Constrained Non-Negative Matrix Factorization for Medical Image Registration

This paper presents a novel medical image registration algorithm named total variation constrained graphregularization for non-negative matrix factorization(TV-GNMF).The method utilizes non-negative matrix factorization by total variation constraint and graph regularization.The main contributions of our work are the following.First,total variation is incorporated into NMF to control the diffusion speed.The purpose is to denoise in smooth regions and preserve features or details of the data in edge regions by using a diffusion coefficient based on gradient information.Second,we add graph regularization into NMF to reveal intrinsic geometry and structure information of features to enhance the discrimination power.Third,the multiplicative update rules and proof of convergence of the TV-GNMF algorithm are given.Experiments conducted on datasets show that the proposed TV-GNMF method outperforms other state-of-the-art algorithms.

A Binary Images Watermarking Algorithm Based on Adaptable Matrix

A watermarking algorithm of binary images using adaptable matrix is presented. An adaptable matrix is designed to evaluate the smoothness and the connectivity of binary images. The watermark is embedded according to the adaptable matrix in this algorithm. In the proposed watermarking algorithm, each image block implements a XOR operation with the binary adaptable matrix, which has the same size with the image block, and in order to embed the watermark data, a multiplication operation are also implemented with the weight matrix. The experimental results show that proposed scheme has a good performance.

Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix

In recent years,binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security.In most state-of-the-art binary image steganographic schemes,they always find out the flippable pixels to minimize the embedding distortions.For this reason,the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain.However,the distortion maps can be calculated for cover and stego images and the difference between them is significant.In this paper,a novel binary image steganalytic scheme is proposed,which is based on distortion level co-occurrence matrix.The proposed scheme first generates the corresponding distortion maps for cover and stego images.Then the co-occurrence matrix is constructed on the distortion level maps to represent the features of cover and stego images.Finally,support vector machine,based on the gaussian kernel,is used to classify the features.Compared with the prior steganalytic methods,experimental results demonstrate that the proposed scheme can effectively detect stego images.

Image Fusion Based on Complex Contourlet Transform and Nonnegative Matrix Factorization

An image fusion method combining complex contourlet transform(CCT) with nonnegative matrix factorization(NMF) is proposed in this paper.After two images are decomposed by CCT,NMF is applied to their highand low-frequency components,respectively,and finally an image is synthesized.Subjective-visual-quality of the image fusion result is compared with those of the image fusion methods based on NMF and the combination of wavelet /contourlet /nonsubsampled contourlet with NMF.The experimental results are evaluated quantitatively,and the running time is also contrasted.It is shown that the proposed image fusion method can gain larger information entropy,standard deviation and mean gradient,which means that it can better integrate featured information from all source images,avoid background noise and promote space clearness in the fusion image effectively.

Reinforced copper matrix composites with highly dispersed nano size TiC in-situ generated from the Carbon Polymer Dots

In order to uniformly disperse the ceramic reinforcements synthesized in-situ in the copper matrix composites,this study used Carbon Polymer Dot(CPD)as the carbon source and Cu–1.0%Ti alloy powder as the matrix for supplying Ti source to prepare in-situ synthesized TiC/Cu composites.The results show that TiC nano-precipitates,having the similar particle sizes with the CPD,form at the grains interior and grain boundaries,and maintain a uniform distribution state.Compared with the matrix,0.3 wt%CPD/Cu composite displays the best strengthplastic compatibility,the ultimate tensile strength achieves 385 MPa accompanied with a corresponding elongation of 21%,owing to the dislocation hindrance caused by nano-carbide and excellent interface bonding between nano TiC and the Cu matrix.The density function theory calculation supports our experimental results by showing a tighter and stronger interface contact.This work presents a new approach for studying in-situ carbide precipitates.

Promote the Compression Efficiency of Digital Images by Using Improved CUR Matrix Decomposition Algorithm

In order to overcome the problem that the CUR matrix decomposition algorithm loses a large amount of information when compressing images, the quality of reconstructed images is not high, we propose a CUR matrix decomposition algorithm based on standard deviation sampling. Because of retaining more image information, the reconstructed image quality is higher under the same compression ratio. At the same time, in order to further reduce the amount of image information lost during the sampling process of the CUR matrix decomposition algorithm, we propose the SVD-CUR algorithm. The experimental results verify that our algorithm can achieve high image compression efficiency, and also demonstrate the high precision and robustness of CUR matrix decomposition algorithm in dealing with low rank sparse matrix data.

Research on Image Quality Enhancement Algorithm Using Hessian Matrix

The Hessian matrix has a wide range of applications in image processing,such as edge detection,feature point detection,etc.This paper proposes an image enhancement algorithm based on the Hessian matrix.First,the Hessian matrix is obtained by convolving the derivative of the Gaussian function.Then use the Hessian matrix to enhance the linear structure in the image.Experimental results show that the method proposed in this paper has strong robustness and accuracy.

Data Matrix二维条形码解码器图像预处理研究

DM码是一种常见的二维条形码,图像预处理是DM码解码器自动识别过程中的重要步骤。提出一种实用的DM码识别图像预处理方法。它没有使用传统的边缘检测和直线检测手段,因此受背景噪声、几何失真的影响较小。此外,使用了校正铁路线坐标,并按区域取样生成码流,显著提高了DM码的识别速度和识别率。实验结果表明,该算法可以克服DM码识别过程中易受噪声干扰、光照不均和几何失真等影响的问题。

基于旋转采集Data Matrix码序列图像拼接方法

针对刀具柱面Data Matrix码图像拼接的特殊需求,已有算法拼接结果识读率低、实时性差的缺陷,提出了一种基于Data Matrix码图像特征的拼接方法.该方法基于缝隙内旋转采集的刀具柱面Data Matrix码序列图像,通过条码纵向位移校正与模块划分,完成基于模块信息的最小欧氏距离图像粗配准和归一化互相关图像精配准;为了保证条码结构正确,消除无重合区域对图像拼接的影响,根据匹配度先将序列图像融合成3部分并校正畸变;最后将这3部分按条码模块关系融合成一幅尺寸正确的图像,实现了条码定位、模块划分,以方便后续进行解码.实验结果表明,文中方法能够满足刀具柱面Data Matrix码序列图像的拼接需求,拼接结果解码正确率达到96%,拼接时间小于250ms,并且大大提高了解码速度.

激光选区熔化成形TC4锥形管的仿真模拟研究

使用Simufact Additive软件建立TC4锥形管的有限元模型,通过工艺仿真进行参数对比试验,最终选择激光功率310W、扫描速度1000mm/s、层厚0.05mm。通过查看应力场、形变量结果辅助设计环节进行结构优化,在更换支撑方案后,建造环节的总形变量降至0.16mm,降低了71%。在全流程仿真下,热处理、线切割、支撑打磨阶段使变形量达到1.07mm。对BCC点阵的胞元结构进行优化,并以迭代前后的杨氏模量为评估指标,通过均质化有限元法进行预测。结果表明:加强后胞元的杨氏模量由405.4MPa提升至434.9MPa,同时由于强化点与零件无接触,所以未增加后处理难度。

Projection registration of X-ray image and CT image

A methodology for alignment of an X-ray image and a CT image, based on the Chamfer 3-4 distance transform and simulated annealing optimization algorithm is presented. Firstly, an initial transformation matrix is constructed. For the convenience of computing, geometric models of the X-ray device to reconstruct the calibration matrix are used. Then, by defining the distance between the 3-D protective and the 2-D object image, we optimize this distance matching problem, using the simulated annealing algorithm. This method is also integrated into medical intra-operation, dealing with the data set acquired from 3-D image workstation and active navigation.

PREPARATION AND CHARACTERIZATION OF WATER-SOLUBLE NEAR-INFRARED EMITTING PbS QUANTUM DOTS

A new facile method for preparing water-soluble near-infrared （NIR）-emitting PbS quantum dots （QDs） is proposed by using N-acetyl-L-cysteine （NAC, a derivate of L-cysteine） as its stabilizer. The influence of the precursor Pb/S molar ratio, the Pb/NAC molar ratio, and the pH of original solution on optical properties is explored. Results show that aqueous PbS QDs with strong NIR fluorescence can be prepared and their photoluminescence emission peaks can be tuned from 895 nm to 970 nm. Studies indicate that such aqueous QDs have a potential application in biomedical imaging, especially in noninvasive in vivo fluorescence imaging. In addition, the resulting PbS QDs are further characterized by a transmission electron microscopy and X-ray diffraction analysis.

基于Matrix VB的数字图像处理教学演示软件

数字图像处理教学演示软件对于数字图像处理课程的建设具有重要的意义,如果使用MATLAB或者其它软件开发工具来进行开发,软件的开发周期长,发布较麻烦。在介绍MatrixVB的基础上,给出了利用MatrixVB在VisualBasic下进行数字图像处理教学演示软件的方法和步骤。

保留反应性软组织联合脱矿牙本质基质应用于拔牙位点保存

背景:反应性软组织内的干细胞间充质具有促进组织再生的潜力,脱矿牙本质基质具有良好的生物相容性,可以作为位点保存术的支架材料,促进骨细胞的附着、增殖和分化。目的:影像学分析拔牙保留反应性软组织1个月后、行脱矿牙本质基质位点保存术后6个月牙槽骨高度和宽度的变化。方法:纳入38例患者共62个拔牙位点,拔除患牙保留反应性软组织1个月后应用脱矿牙本质基质行位点保存术,术前、术后即刻、术后6个月拍摄锥形束CT,分别测量近中骨高度、中央骨高度、远中骨高度、颊侧骨高度、舌侧骨高度、牙槽嵴宽度,根据拔牙后剩余牙槽窝骨壁数量分为一壁骨缺损、二壁骨缺损、三壁骨缺损、四壁骨缺损。比较位点保存术前、术后即刻、术后6个月的骨量变化。结果与结论:①在骨愈合期间无位点发生创口感染;②与位点保存术前比较,术后即刻骨高度、骨宽度明显增加(P<0.05);术后6个月骨高度增加(P<0.05),骨宽度无明显变化(P>0.05);与术后即刻比较,术后6个月骨宽度吸收了(1.253±2.896)mm(P<0.05),骨高度无明显变化(P>0.05);③位点保存术后即刻、术后6个月4种骨缺损类型的骨高度明显增加(P<0.05),骨宽度无显著变化(P>0.05);术后6个月较术前一壁骨缺损近中骨量增长最少(P<0.05),二壁骨缺损近中骨量增长最多(P<0.05);④结果表明:脱矿牙本质基质应用于位点保存术可有效预防和减缓拔牙术后的牙槽骨吸收,能够在一定程度上重建已发生吸收的牙槽骨轮廓;拔牙术后保留反应性组织应用于脱矿牙本质基质位点保存术中,可实现创口封闭,临床疗效好;脱矿牙本质基质应用于一壁、二壁、三壁、四壁牙槽窝位点保存效果相似,但总体而言,脱矿牙本质基质应用于骨壁完整的拔牙窝时位点保存效果更为优良。

二维电离室点矩阵Matrixx在调强验证中的应用

目的：利用I′mRTMatrixx对适形及调强放射治疗计划二维剂量平面进行验证。通过软件分析确定治疗计划的准确性,提高治疗质量。方法：用Matrixx二维电离室点矩阵系统对适形调强放疗计划进行验证测试,模体为等效固体水,把Matrixx上面加到4.7 cm等效固体水,下面垫5 cm等效固体水,放入CT进行扫描,在计划系统中建成QA模体。然后将治疗计划系统中的适形调强计划放到QA模体上进行特定深度的计算,得到一个剂量平面计划,将该计划输入分析软件中,与同样条件下的实测剂量平面进行分析,比较。结果：通过软件采用Gamma算法,剂量偏差3%,位置偏差3 mm,小于1的r值是96%~100%。结论：Ma-trixx二维电离室点矩阵,在临床中可作为适形计划和调强计划的相对剂量验证工具,而且简单高效。是放疗质量控制的理想剂量验证工具。利用Matrixx阵列能同时较好的实现其绝对剂量和相对剂量的测量。

基于时空粒子图像的管道流速测量方法及验证

管道流速测量除了得到流动方向的平均速度,有时还需要得到垂直流动方向的速度分布。该文提出一种新的光学非接触测量方法——一维粒子图像测速法(one-dimensional particle image velocimetry,1D-PIV),利用垂直于流动方向粒子的一维空间信息和时间信息构建时空状态矩阵,相关上下游两处时空状态矩阵即可完成平均流速和流速分布的测量。以DN35 mm直管搭建实验测试系统,在颗粒浓度为0.04 g/L条件下测量流速范围为84.99~261.10 mm/s的管道流,以单粒子追踪测速法(single particle tracking,SPT)作比对,1D-PIV测量的平均流速最大相对误差为2.67%,速度剖面最大相对误差为近壁面的1.73%。实验结果证明1D-PIV是一种简单有效的管道流速测量方法。