采用轮廓特征匹配的红外-可见光视频自动配准

为了精确地配准近平面场景下的红外-可见光视频序列,本文提出了一种基于轮廓特征匹配的自动配准方法,通过迭代匹配目标轮廓特征来解决异源图像中配准特征的提取和匹配难题。首先,采用运动目标检测技术获取目标轮廓,并由曲率尺度空间(CSS)角点检测算法提取轮廓特征点。此后,建立全局形状上下文描述子和局部边缘方向直方图描述子描述特征,从而实现可靠的特征匹配。来自不同时刻的匹配点对被保存在一个基于高斯距离准则的特征匹配库中。最后,为了克服近平面场景中目标深度变化的影响,本文结合前景样本随机抽样策略计算配准矩阵的损失函数,完成对全局配准矩阵的更新。在LITIV数据库上对方法进行实验验证,结果表明本文方法的配准精度优于当前先进的对比方法,在9个测试视频上的平均重叠率误差仅为0.194,与对比方法相比下降了18.5%。基本满足了近平面场景下红外-可见光视频序列配准的精度要求,且具有较高的鲁棒性。     

Colored apparel and its potential influence on heterosexual attraction

The objective of this study is to determine if men would follow the “red effect” when choosing colors for women to wear on a date, and also to determine if the colors that men would wear when going on a date would be the same as the colors that females (their date) would wish them to wear. A set of psychophysical data was generated from this experiment, where participants were asked to rank a set of 10 colored samples based on preference for each question asked. There were three different sets of colored samples. The set of colored samples given to the participant depended on the question. A total of five questions were asked. Scaling analysis was done on the data to organize a set of items according to preferences providing values, an interval scale (Z values), that correspond to the relative perceptual differences among the stimuli. The Z values were graphed to show the general preference of colors for women to wear, and the preference of colors for men to wear. A Spearman's rank-order correlation coefficient (SRCC) was calculated comparing each individual's rank order with the mean rank order for that specific question. An average Spearman's rank order was calculated for each question and each gender in order to determine the variability in answers. Scaling results indicate that men follow the “red effect,” but women preferred to wear other colors such as turquoise, blue, or yellow depending on the outfit. Males and females agreed that no matter the colored bottoms (denim or black), blue was the preferred color top for men to wear. SRCC results showed a lot of variability between individual answers and the mean answer indicating that participants' rankings did not necessarily agree with general color preferences presented in the scaling analysis. While scaling analysis might suggest certain color preferences such as men following the “red effect” and women preferring to wear blue, the poor correlation found using SRCC between the individual answers and the mean rank orders suggests that color preferences for each individual are inherently unique.     

正弦波纹挡板式沉降器内流动特性

采用VOF模型对正弦波纹式入口挡板的重力非均相沉降器内流场进行数值模拟研究。对比了正弦波纹挡板与平挡板的平均流场分布情况，分析了沉降器的轴向流速均一程度（λ₁）随时间演化特性，探究了λ₁和面积加权平均湍流强度（I_a）在沉降器内空间分布特性；引入流场均稳指标USC，研究了冲击间距（L_b/D）对USC的影响。结果表明：正弦波纹挡板作为入口构件可以有效降低返混。在0.84＜L_b/D＜2.17范围内，正弦波纹板沉降器内流场的均一程度整体高于平面挡板；随着L_b/D减小，平挡板沉降器内流场的λ₁基本不变，但正弦波纹挡板沉降器内流场的λ₁降低，且对I_a的影响不明显。对比平挡板，正弦波纹挡板可以有效降低轴向速度的梯度，使返混区面积减小，流场稳定性提高。随着L_b/D增加，USC值呈现多峰值趋势，L_b/D=2.17时正弦波纹板沉降器的USC取得极大值为14.68，较平挡板提高了93.67%。     

基于深度语义分割的多源遥感图像海面溢油监测

针对遥感图像海面溢油区域通常受到斑噪声以及强度不均等因素的影响,从而导致溢油区域监测效果较差的问题,本文引入了深度语义分割的方法,将深度卷积神经网络与全连接条件随机场相结合,形成端对端连接。以Resnet结构为基础,首先通过深度卷积神经网络对多源遥感图像粗分割并作为输入,然后经过改进的全连接条件随机场,利用高斯成对势和平均场近似定理,建立条件随机场形成递归神经网络作为输出。通过多源遥感图像对海面溢油区域进行监测,并利用可见光图像估计溢油区域面积。实验在所建立的多源遥感图像数据集上与其它先进模型进行对比,结果表明本文方法提高了溢油区域的分割精度以及精细细节程度,平均交并比为82.1%,监测效果具有明显地改善。     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Image analysis applications on assessing static stability and flowability of self-consolidating concrete

A digital image processing (DIP) method associated with a MATLAB algorithm is used to evaluate cross sectional images of self-consolidating concrete (SCC). Two new parameters, such as inter-particle spacing of coarse aggregate and average mortar-to-coarse aggregate ratio, defined as average mortar thickness index (MTI), were proposed to quantitatively evaluate the static stability of SCC. Statistical models were developed to predict flowability of SCC mixtures. Test results revealed that the proposed DIP method and MATLAB algorithm can be successfully used to derive inter-particle spacing and MTI and quantitatively evaluate the static stability on hardened SCC samples. A probability density of 60% from histogram analysis appears to be a reasonable threshold for indicating a uniformly distributed SCC mixture. For a given mortar yield stress, a critical mortar viscosity of 1.30 Pa s tends to significantly affect the trend of slump flow changing with MTI. The investigated relationship between parameters measured from DIP method and existing theoretical frames is well correlated. The outcome of this study can be of practical value for providing an efficient and useful tool in designing mixture proportions of SCC.     

Kernel-based fourth-order diffusion for image noise removal

The fourth-order partial differential equations have good performance on noise smoothing and edge preservation without creating blocky effects on smooth regions. However, for low signal-to-noise ratio images, the discrimination between edges and noise is a challenging problem. A novel kernel-based fourth-order diffusion is proposed in this paper. It introduces a kernelized gradient operator in the fourth-order diffusion process, which leads to more effective noise removal capability. Experiment results show that this method outperforms several previous anisotropic diffusion methods for noise removal and edge preservation.     

天然染料银杏叶染亚麻纱的染色性能研究

以天然染料银杏叶为原料,采用微波提取法进行染料原液的提取,并以提取后的原液作为染料原液对28 tex亚麻纱进行染色,采用p H、染色温度、媒染剂用量、渗透剂用量4个因素分析染色效果,以单因素分析结果作为基础,进行4因素3水平的正交试验,将正交试验后的染色纱样进行色牢度测定。研究结果表明,染色最佳工艺条件为:渗透剂用量1.5 m L,媒染剂用量5 m L,染色p H 7,染色温度80℃,亚麻纱染色后的色牢度达到3级以上。     

Color preferences for different topics in connection to personal characteristics

Studies on color preferences are dependent on the topic and the relationships with personal characteristics, particularly personality, but these are seldom studied in one population. Therefore a questionnaire was collected from 1095 Dutch people asking for color preferences about different topics and relating them to personal characteristics. Color preferences regarding different topics show different patterns and significant differences were found between gender, age, education and personality such as being technical, being emotional or being a team player. Also, different colors were mentioned when asked for colors that stimulate to be quiet, energetic, and able to focus or creative. Probably, due to unconsciousness of contexts, many people had no color preference, a result that in the literature seldom is mentioned. Blue was the overall favorite color; however, most males chose for blue (25%) while most females had no color preference (18%). Black was the overall favorite color for clothing, mainly chosen by females (40%), while males primarily chose blue (27%). For building interiors subjects preferred white. For moods, subjects preferred white for being quiet or being able to focus, red for being energetic and had no color preference for being creative. It is concluded that color preferences are dependent upon the topic, and personal characteristics. The findings are important for architects, interior designers, fashion designers and product designers to have a basic idea of preferred colors for different objects by different types of people. © 2013 Wiley Periodicals, Inc. Col Res Appl, 40, 62–71, 2015