A MULTI-SCALE MORPHOLOGICAL APPROACH TO SAR IMAGE EDGE DETECTION

This paper introduces a multi-scale morphological edge detection algorithm to extract SAR image edge which suffers seriously from noise. Combining the basic theme of morphology with that of multi-scale analysis, the algorithm presents the outstanding characteristics of accuracy and robustness. Comparative Experiments reveal its fine performance.

A Semi-Vectorial Hybrid Morphological Segmentation of Multicomponent Images Based on Multithreshold Analysis of Multidimensional Compact Histogram

In this work, we propose an original approach of semi-vectorial hybrid morphological segmentation for multicomponent images or multidimensional data by analyzing compact multidimensional histograms based on different orders. Its principle consists first of segment marginally each component of the multicomponent image into different numbers of classes fixed at K. The segmentation of each component of the image uses a scalar segmentation strategy by histogram analysis;we mainly count the methods by searching for peaks or modes of the histogram and those based on a multi-thresholding of the histogram. It is the latter that we have used in this paper, it relies particularly on the multi-thresholding method of OTSU. Then, in the case where i) each component of the image admits exactly K classes, K vector thresholds are constructed by an optimal pairing of which each component of the vector thresholds are those resulting from the marginal segmentations. In addition, the multidimensional compact histogram of the multicomponent image is computed and the attribute tuples or ‘colors’ of the histogram are ordered relative to the threshold vectors to produce (K + 1) intervals in the partial order giving rise to a segmentation of the multidimensional histogram into K classes. The remaining colors of the histogram are assigned to the closest class relative to their center of gravity. ii) In the contrary case, a vectorial spatial matching between the classes of the scalar components of the image is produced to obtain an over-segmentation, then an interclass fusion is performed to obtain a maximum of K classes. Indeed, the relevance of our segmentation method has been highlighted in relation to other methods, such as K-means, using unsupervised and supervised quantitative segmentation evaluation criteria. So the robustness of our method relatively to noise has been tested.

Morphology Similarity Distance for Bearing Fault Diagnosis Based on Multi-Scale Permutation Entropy

Bearings are crucial components in rotating machines,which have direct effects on industrial productivity and safety.To fast and accurately identify the operating condition of bearings,a novel method based on multi⁃scale permutation entropy(MPE)and morphology similarity distance(MSD)is proposed in this paper.Firstly,the MPE values of the original signals were calculated to characterize the complexity in different scales and they constructed feature vectors after normalization.Then,the MSD was employed to measure the distance among test samples from different fault types and the reference samples,and achieved classification with the minimum MSD.Finally,the proposed method was verified with two experiments concerning artificially seeded damage bearings and run⁃to⁃failure bearings,respectively.Different categories were considered for the two experiments and high classification accuracies were obtained.The experimental results indicate that the proposed method is effective and feasible in bearing fault diagnosis.

Morphology Difference between the Alkali Activated Cement and Portland Cement Paste on Multi-scale

The features of alkali activated slag（AAS） and portland cement （PC） were observed on multi-scale,the crack and fracture sections were observed with naked eyes,and SEM and AFM were used to study the structure morphology differences between PC and AAS on micrometer to nano meter scale.The experimental results indicated that the AAS paste had soil like fracture texture and it was composed of mainly C-S-H gel but lacks of crystals,and it had a very strong tendency to shrink and crack.AAS paste is much denser and more homogeneous than PC,and on the nano scale C-S-H nano particle in the AAS paste is much smaller and packs much denser than PC paste.

Light Absorption Characteristics of Multi-Morphology FeS_2 Granular Synthesized Under Hydrothermal Conditions

A. Ennaoui proposed that FeS2 owns an appropriate band gap (0.95 eV) and large absorption coefficient, it can be used for solar materials. People had studied the light absorption characteristics of the FeS2 prepared by different methods, and believed that crystal grain size, defect density and crystalline quality are important factors that affect the light absorption properties. In order to take a depth study of the absorption properties, the research group has taken a study on light absorption characteristics of natural pyrite, the existence of Co, Ni impurities results in lower band gap and conversion efficiency.

An image registration method based on multi-resolution morphology contour detection

Combined with the printing application,an image registration method based on the multi-resolution morphology contour detection was proposed.First,a direction based multi-resolution gray morphology in the scheme was proposed to realize the contour extraction.Then,based on the contour features,the subspace image registration was proposed to deal with issues of the computing complexity appeared in the traditional image registration methods.The proposed image registration was efficiently applied in the defect inspection of printing images.

Seismic energy dispersion compensation by multi-scale morphology

Seismic energy decays while propagating subsurface, which may reduce the resolution of seismic data. This paper studies the method of seismic energy dispersion compensation which provides the basic principles for multi-scale morphology and the spectrum simulation method. These methods are applied in seismic energy compensation. First of all, the seismic data is decomposed into multiple scales and the effective frequency bandwidth is selectively broadened for some scales by using a spectrum simulation method. In this process, according to the amplitude spectrum of each scale, the best simulation range is selected to simulate the middle and low frequency components to ensure the authenticity of the simulation curve which is calculated by the median method, and the high frequency component is broadened. Finally, these scales are reconstructed with reasonable coefficients, and the compensated seismic data can be obtained. Examples are shown to illustrate the feasibility of the energy compensation method.

Pollen development and multi-nucleate microspores of Populus bolleana Lauche

Populus bolleana is a variety of P. alba, commonly used in poplar breeding programs in China. Developmental biology that involves staminate flowers, microsporogenesis and microgametogenesis ofP. bolleana is essential for Populus improvement in cross breeding for better characteristics in sexual reproduction. Flower morphology and pollen development were described and illustrated using anatomical, sectioning and stain-clearing techniques. The results show that microsporocytes undergo a regular meiotic process, but some multi-nucleate microspores occur at the microspore stage. It takes five days for microsporocytes to develop to mature pollen by forcing flower branches under greenhouse conditions. Additionally, an important relationship was found between stages of meiosis and anther colors. Microspore tetrads formed when the anther color turned yellow, whereas, when the pollen matured, the anther was red and the tapetum degenerated completely. When mature pollen grains are formed, flower buds develop into male catkins. In the end, filament elongated and pollen grains were released from dehisced anthers.

Structure and Tribological Properties of CrTiAlN Coatings Deposited by Multi-Arc Ion Plating

CrTiAIN coatings were prepared by using a home-made industrial scale multi-arc ion plating system. The coatings were found to be composites of face-center-cubic CrN and TiN. The surface roughness, microhardness, and tribological properties of the films were significantly affected by the nitrogen pressure and dc-pulsed bias voltage applied to the substrate. The CrTiA1N coatings with the smoothest surfaces were obtained at optimum conditions of nitrogen pressure of 5.0 Pa and bias voltage of -200 V. The samples were found to exhibit a hardness of 2900 HV0.05 with an average friction coefficient of 0.16 and wear rate of 1.5× 10^-16 m^3/N.m against cemented carbide.

An infrared and visible image fusion method based upon multi-scale and top-hat transforms

The high-frequency components in the traditional multi-scale transform method are approximately sparse, which can represent different information of the details. But in the low-frequency component, the coefficients around the zero value are very few, so we cannot sparsely represent low-frequency image information. The low-frequency component contains the main energy of the image and depicts the profile of the image. Direct fusion of the low-frequency component will not be conducive to obtain highly accurate fusion result. Therefore, this paper presents an infrared and visible image fusion method combining the multi-scale and top-hat transforms. On one hand, the new top-hat-transform can effectively extract the salient features of the low-frequency component. On the other hand, the multi-scale transform can extract highfrequency detailed information in multiple scales and from diverse directions. The combination of the two methods is conducive to the acquisition of more characteristics and more accurate fusion results. Among them, for the low-frequency component, a new type of top-hat transform is used to extract low-frequency features, and then different fusion rules are applied to fuse the low-frequency features and low-frequency background; for high-frequency components, the product of characteristics method is used to integrate the detailed information in high-frequency. Experimental results show that the proposed algorithm can obtain more detailed information and clearer infrared target fusion results than the traditional multiscale transform methods. Compared with the state-of-the-art fusion methods based on sparse representation, the proposed algorithm is simple and efficacious, and the time consumption is significantly reduced.

基于多视角图像形态颜色纹理特征融合的生物量获取

可见光成像以其快速、经济和非破坏性等优势,正成为高通量植物表型和遗传研究的有效工具,但仍有待解决基于可见光图像评估肉眼不可见的产量表型特性。本文针对植物叶片遮挡重叠及变量尺度单一导致图像数据精度受限的问题,提出了一种利用多视角图像融合多类别特征评估高粱地上生物量的技术方法。对15个种质基因的300株高粱进行了双因素(水分和养分)双水平(高和低)试验。基于旋转平台,利用可见光相机对每株高粱等角度间隔自动采集10幅侧视图像和1幅俯视图像,通过植物掩膜图像提取每株高粱形态特征(俯视、侧视投影面积)、颜色特征(RGB像素值)与纹理特征(均值、协方差、同质性等),将多个视角下的信息平均化处理,并基于图像R、G、B像素值构建16个颜色植被指数。结果表明,相对于考虑单一类型变量和单视角下的图像信息,基于多视角平均化图像信息融合形态、纹理、颜色特征能显著增加对高粱地上生物量表型的获取能力。利用SVR、RF、BPNN算法融合21组优化图像数据变量构建高粱地上生物量回归模型,精度最高的RF算法模型测试集决定系数R2为0.881,均方根误差(RMSE)为60.714 g/m^(2),平均绝对误差(MAE)为42.364 g/m^(2)。为进一步优化RF算法模型的参数,选取GA、GS、SSA对RF算法模型进行超参数寻优。结果表明,SSA-RF优化模型测试集R2提升至0.902,RMSE为48.706 g/m^(2),MAE为39.877 g/m^(2)。基于多视角图像形态-颜色-纹理特征融合能从有限的信息中衍生得到更多有效信息用于估测高粱地上生物量,从而为高粱生长监控、胁迫检测、水肥精确施用和良种快速筛选提供理论依据和技术支持。

基于节能导向的寒冷地区医院建筑形态多目标寻优技术研究

建筑设计行业面临着能源需求不断增长的挑战,建筑模拟被广泛用于后期设计阶段.虽然早期阶段的设计已被证实会对建筑的整体性能产生重要影响,其在早期阶段设计决策对最终的建筑性能和成本有重大影响,但其应用仍然是有限的.本文提出了一种新的设计模拟方法,以节能导向为目标,遗传算法Octopus为工具,参数化模拟Grasshopper为平台,寒冷地区为背景,将参数化建模与多目标优化结合起来,以便实现快速迭代和权衡分析.综合考虑医院建筑功能的特殊性和多项限制条件,从总图布局、建筑单体和建筑局部三个方面分别进行变量控制,将节能纳入早期建筑设计的考虑要素中,并将医院建筑形态多目标寻优技术应用于实际工程项目中,有助于建立一套目标导向-自动寻优-设计决策的仿真模拟框架,该框架有利于主动、智能和基于经验的建筑仿真模拟,有助于在建筑设计早期做出决策.

基于多形态学成分分析的图像融合

将多尺度分解与稀疏表示相结合,提出了一种基于多形态学成分分析(MCA)的图像融合算法。采用基于联合稀疏表示(JSR)的方法融合卡通子图像中的冗余和互补信息,并利用基于方向特征的方法融合具有更多细节信息和噪声的纹理子图像。结果表明,提出的图像融合算法在主观视觉效果和客观评价指标上均优于先进的图像融合算法。

酒瓶椰子叶枯病病原菌鉴定

【目的】近年来,福建省厦门市园林植物园内的酒瓶椰子频发叶枯病,影响了植株的正常生长,降低了酒瓶椰子的观赏价值。为了更好地防控酒瓶椰子叶枯病,对引起该病害的病原菌进行了种类鉴定。【方法】从厦门市园林植物园收集了12份染病的酒瓶椰子叶片样品,通过分离和纯化,得到5个类拟盘多毛孢属真菌菌株。结合其形态特征和基于3个基因(ITS、TUB2和TEF1)的系统发育分析结果将这5个菌株鉴定到种。最后用柯赫氏法则验证所得菌株的致病性。【结果】这5个菌株被鉴定为Neopestalotiopsis cubana、Pestalotiopsis diploclisiae、P.humicola、P.neolitseae和Pseudopestalotiopsis theae。柯赫氏法则验证结果显示,N.cubana、P.diploclisiae、P.humicola和Ps.theae可以引起酒瓶椰子叶片发病,而P.neolitseae不能侵染酒瓶椰子的叶片。【结论】N.cubana、P.diploclisiae、P.humicola和Ps.theae是引起酒瓶椰子叶枯病的病原菌。这是新拟盘多毛孢属(Neopestalotiopsis)和假拟盘多毛孢属(Pseudopestalotiopsis)真菌在酒瓶椰子上的首次报道。其中,N.cubana为我国首次发现。

多维异质结光催化剂g-C_(3)N_(4)/WO_(3)的制备及应用

采用原位热聚合法和溶剂热法分别合成了片状和球状两种g-C_(3)N_(4)/WO_(3)异质结,运用XRD、SEM和UV-Vis DRS等手段进行了表征,并考察了两种异质结对盐酸四环素(TC-HCl)的光催化降解效果。表征结果显示,二维(2D)g-C_(3)N_(4)/WO_(3)呈现堆叠或卷曲的不规则纳米片状,三维(3D)g-C_(3)N_(4)/WO_(3)由大量直径为1~5μm的纳米微球组成。实验结果表明:2D g-C_(3)N_(4)/WO_(3)比3D g-C_(3)N_(4)/WO_(3)具有更强的光催化活性,在TC-HCl质量浓度10 mg/L、光催化剂加入量200 mg/L的条件下,暗反应60 min后,再转用氙灯(500 mW/cm^(2))照射60 min,2D g-C_(3)N_(4)/WO_(3)和3D g-C_(3)N_(4)/WO_(3)对TC-HCl的去除率分别为98.96%和41.15%;在2D g-C_(3)N_(4)/WO_(3)光催化降解TC-HCl的体系中,·O_(2)^(-)、·OH和h^(+)对TC-HCl降解的影响顺序为·O_(2)^(-)>·OH>h^(+)。

含能材料的组装及其性能研究进展

含能材料的形貌及结构对其各项性能具有显著影响,为改善现有含能材料的固有性能,含能材料的组装是一种有效的技术手段。基于国内外学者的相关工作,从单一组分含能材料通过组装直接影响结构从而调控其性能、多组分复合含能材料的组分及复合结构协同调控性能两个角度出发,综述了当前含能材料的组装方法及其对性能的调控效果,阐述了其它功能材料组装对含能材料的启示。当前,单一组分含能材料组装可以带来新的炸药形貌,多组分组装可以弥补现有性能调控的不足,实现能量及安全性能协同提升,但含能材料的组装发展还面临着组装方法单一、过程调控难、组装机制尚不明确、多组分研究不够深入等问题。未来研究可以重点关注含能材料晶体组装理论完善、微介观表征技术发展及新组装技术探索三个角度。

顾及形态特征的遥感影像湖泊多分辨率表达方法

遥感影像的多分辨率表达在数据传输、计算效率和隐私保护方面发挥着重要作用。传统的遥感影像多分辨率表达方法忽略了目标的整体形态特征,容易产生信息冗余,影响图像的易读性。结合超像素分割和纹理迁移技术,文章提出了一种顾及形态特征的遥感影像多分辨率表达方法。该方法首先根据地理特征差异和分形维数对湖泊形态特征进行了分析。然后,基于超像素分割算法对湖泊边界进行了简化。最后,利用原始和简化湖泊边界进行纹理迁移,生成多分辨率遥感影像。结果表明,该方法在遥感影像多分辨率表达过程中能够有效去除冗余细节,提高对象的易读性。

基于GA的灰铸铁表面激光熔覆316 L工艺参数优化

为了提升HT250灰铸铁材料的综合性能,采用遗传算法对多目标工艺参数进行优化,得出相应经验参数组,在灰铸铁材料表面进行激光熔覆316L合金实验;采用数字化检测仪器,根据试样几何形状、宏观形貌、硬度等变化规律,得出最优工艺参数组。结果表明,当设置送粉速率为0.25 g/s、扫描速率为10 mm/s、激光功率为2800 W时,316L熔覆层表面几何形状最佳,宏观形貌好,洛氏硬度最大值达37.6 HRC,试样熔覆性能良好。这一结果综合提高了灰铸铁的各项性能,为灰铸铁产品磨损后的修复再利用提供实践参考。

小天体附着形貌特征快速优选

针对小天体附着过程中形貌特征复杂且数量众多,导致在线特征选取时特征组合数量多、计算量大、计算效率低等问题,提出了一种在线形貌特征快速选取方法。利用多类型特征快速评价指标结合搜索区域,建立了单帧图像特征快速优选的方法。同时,考虑到小天体附着过程中在线特征选取采样间隔短、帧间图像重合度高、特征继承概率高的特点,提出了帧间图像特征继承优选方法。仿真实验表明单帧图像搜索区域和帧间图像特征继承的设计,降低了特征组合数量,提升了计算效率,提高了在线特征选取速度。

基于多特征融合卷积的步态识别算法研究

针对GaitSet算法中主干网络学习能力和分类能力较弱,提出基于多特征融合卷积网络的步态识别算法(MFFC-GaitSet)。算法通过多特征融合卷积重建GaitSet网络增强网络学习能力,同时对三元组损失函数进行平滑优化;利用形态学处理对步态轮廓图进行修补。算法在Casia-B数据集上进行验证,步态识别精度达到85.811%,提高2.6%;模型权重仅增加6%。算法可以有效减少复杂环境对步态识别的负面影响,实现复杂环境下高精度的步态识别。实验结果表明,方法能够实现较为精确的步态识别,并具有较佳的鲁棒性和泛化能力。