Welding deviation detection method based on weld pool image contour features

Automatic on-line detection of welding deviation based on machine vision is one of the key technologies of arc welding robot tracking welding,in which obtaining high quality weld pool image and accurate welding deviation detection algorithm are two important steps of tracking welding.Through the research and analysis of the weld pool image of gas metal arc welding(GMAW),it was found that the weld pool contains abundant welding information.First,the average gray value of the weld pool image can reflect the interference degree of arc to weld pool image and the heat input of welding process.Secondly,the tip of the weld pool image contour can reflect the center of the groove gap.Finally,the horizontal distance between the center coordinate of the wire contour and the tip coordinate of the weld pool image contour can reflect the welding deviation.On the basis of analyzing the characteristics of weld pool image,this paper proposes a new method of weld seam deviation detection,which includes the collection of weld pool image,image preprocessing,contour extraction and deviation calculation.The results of the tests and analyses showed that the maximum error of the on-line welding deviation obtained was about 2 pixels(0.17 mm)when the welding speed was≤60 cm/min,and the algorithm was stable enough to meet the requirements of real-time deviation detection for I-groove butt welding.The method can be applied to the on-line automatic welding deviation detection of arc welding robot.

Perceptual Gradient Similarity Deviation for Full Reference Image Quality Assessment

Perceptual image quality assessment(IQA)is one of the most indispensable yet challenging problems in image processing and computer vision.It is quite necessary to develop automatic and efficient approaches that can accurately predict perceptual image quality consistently with human subjective evaluation.To further improve the prediction accuracy for the distortion of color images,in this paper,we propose a novel effective and efficient IQA model,called perceptual gradient similarity deviation(PGSD).Based on the gradient magnitude similarity,we proposed a gradient direction selection method to automatically determine the pixel-wise perceptual gradient.The luminance and chrominance channels are both took into account to characterize the quality degradation caused by intensity and color distortions.Finally,a multi-scale strategy is utilized and pooled with different weights to incorporate image details at different resolutions.Experimental results on LIVE,CSIQ and TID2013 databases demonstrate the superior performances of the proposed algorithm.

Simple schizophrenia revisited: Its schizophrenic body image deviation

Simple schizophrenia has not yet been recognized as a well-established diagnostic category as one of the subtypes of schizophrenia, however, its inclusion to the official diagnostic system is regarded as urgent for early intervention. Here, we report our new observation that body image distortion uniquely found in typical schizophrenia, as reflected in the perception of mass of flesh of living objects in the whole or part of the Rorschach stimuli (Koide et al., 2002), was shown in the patients conforming to the original description of simple schizophrenia, to revisit its relatedness to schizophrenia from a cognitive and perceptual point of view. The Rorschach test was administered to four inpatients of a local mental hospital, showing social and occupational decline, negative symptoms and absence of positive symptoms. The presence or absence of Rorschach flesh mass body image percepts was examined. All of four patients revealed Rorschach mass of flesh responses. The fact that simple schizophrenia exhibited the same body image distortion in the flesh mass passive global perception with typical schizophrenia suggests the adequacy of reconsidering simple schizophrenia as a form of schizophrenia.

Development and Parallelization of an Improved 2D Moving Window Standard Deviation Python Routine for Image Segmentation Purposes

Two additional features are particularly useful in pixelwise satellite data segmentation using neural networks: one results from local window averaging around each pixel (MWA) and another uses a standard deviation estimator (MWSD) instead of the average. While the former’s complexity has already been solved to a satisfying minimum, the latter did not. This article proposes a new algorithm that can substitute a naive MWSD, by making the complexity of the computational process fall from O(N2n2) to O(N2n), where N is a square input array side, and n is the moving window’s side length. The Numba python compiler was used to make python a competitive high-performance computing language in our optimizations. Our results show efficiency benchmars

Minimal deviation adenocarcinoma with elevated CA19-9:A case report

BACKGROUND Minimal deviation adenocarcinoma is a rare malignancy with a high rate of misdiagnosis and high aggressiveness,and its diagnosis relies on histopathology.Surgical resection is the preferred and most effective treatment,but the outcomes are often unsatisfactory.CASE SUMMARY A 60-year-old perimenopausal woman was admitted to the hospital and found to have elevated CA19-9 on physical examination without abdominal pain or vaginal bleeding.Clinical examination and positron emission tomography/computed tomography examination were unremarkable,magnetic resonance imaging examination was suggestive of dominant cervical lesions,and methylation examination was suggestive of malignant lesions.Tissue samples were taken from the suspected cervical lesion,and the final pathologic diagnosis was minimal deviation adenocarcinoma.Based on the pathologic diagnosis of suspected minimal deviation adenocarcinoma,radical abdominal total hysterectomy,bilateral oophorectomy,and pelvic and para-aortic lymph node dissection were performed.The final histological report confirmed minimal deviation adenocarcinoma of the cervix,stage IB2,with lymph node metastasis.Minimal deviation adenocarcinoma is a tumor with aggressive clinical behavior.CONCLUSION Patients with minimal deviation adenocarcinoma have a lower survival rate than patients with conventional human papillomavirus-related cervical adenocarcinoma.A precise preoperative pathologic diagnosis may reduce the mortality rate due to missed optimal treatment with multiple surgical interventions.To date,there is no therapeutic consensus;therefore,each case must be treated individually.

Solving the Problem of Silicon Dioxide Melting Based on Deviation Model

In order to reveal the dissolution behavior of iron tailings in blast furnace slag,we studied the main component of silica in iron tailings.First,edge contour features need to be established to represent the melting process of silica.We choose shape,perimeter,area and generalized radius as objects.By independently analyzing the influence of these four indexes on the melting rate,the area and shape were selected as the characteristic parameters of the edge contour of the silica particles.Then,the actual melting rate of the silica is estimated by the edge contour feature index.Finally,we can calculate the melting rate of the first second of three time periods of 0.00010312mm^3/s,0.0002399mm^3/s,0.0000538mm^3/s.

基于互信息量均方差提取关键帧的激光视频图像检索研究

为保证激光视频图像检索结果中不存在重复性冗余图像,提出了基于互信息量均方差提取关键帧的激光视频图像检索方法。基于互信息量均方差的关键帧提取方法,以激光视频图像颜色的互信息量均方差最大化,为激光视频图像关键帧的聚类中心设置标准,以此聚类提取不重复的视频图像关键帧;通过基于关键帧的激光视频图像检索方法,将所提取关键帧作为激光视频图像检索的核心判断内容,提取与所需图像关键帧相似度显著的激光视频图像,完成激光视频图像检索。实验结果显示:此方法使用后,提取的激光视频图像关键帧冗余度仅有0.01,激光视频图像检索结果的MAP指标测试值高达0.98,检索结果中不存在重复性冗余图像。

结合细粒度自注意力的实例图像着色

尽管基于深度学习的图像着色方法已取得显著效果,但仍存在冗余色斑、着色暗淡和颜色偏差三个问题。为此,提出了一种结合细粒度自注意力(fine-grain self-attention,FGSA)的实例图像着色方法。具体地,首先将提取的特征图分为颜色和空间位置,并结合两者拟合提高颜色和图像空间位置的对应关系,以缓解冗余色斑;其次,受光学摄影HDR原理的启发,利用感受野小的卷积核增强或抑制图像的颜色特征,并结合softmax对特征进行动态映射,从而提高对比度,缓解着色暗淡的问题;最后,组合不同的非线性基函数,增加网络对非线性颜色的表达,拟合出最接近真实图像的颜色分布,以解决颜色偏差。大量的实验结果表明,该方法在实例图像着色中取得了良好的效果。特别地,与当前较优的着色方法相比,该方法在特征感知评价指标LPIPS和FID上分别降低了4.1%和7.9%。

基于感性意象聚类的女性健身产品CMF设计研究

通过感性意象研究女性对健身产品CMF(颜色、材质、工艺)的感性需求,并为女性健身产品提供客观准确的设计因素选择提供依据。采用语义差异量表获取产品和CMF的意象,并通过感性意象偏差的衡量,分析不同因素意象与意象标准之间的差异度。基于意象偏差,通过聚类分析方法,获得最佳设计因子组合。分析得出各设计因素最优选择,以及13种与女性健身产品意象匹配高的设计因子组合。凝练得出4种设计因素的设计原则,指导产品设计中因素的选择。依据研究指导设计出的产品符合女性用户的感性需求,有助于产品在使用过程中为女性群体提供更好的情感体验。该研究为在设计过程中把握用户对CMF感性需求提供了新思路、新方法。

基于视觉引导的焊接机器人焊缝纠偏技术的研究

当前焊接机器人因自适应性不足,存在着工件安装误差、间隙变化、热变形等问题,基于视觉引导对焊接机器人焊缝纠偏技术进行研究,通过焊接图像处理、提取特征点、离线在线纠偏等方法实现焊缝的跟踪与校正,改善工件焊接质量。

基于图像重建的代谢肿瘤总体积分级模型

总体代谢肿瘤体积(TMTV)是一种较为重要的独立于其他指标的预后指标,对患者的准确治疗具有十分重要的指导作用。准确确定TMTV的分级是一项极具挑战的任务,为此文章提出基于图像重建的代谢肿瘤总体积分级模型,其中包含两个模块:分割辅助多维特征学习模块(SAMFL)和重建纠正模块(RCM)。前者通过优化和融合分割特征获得更加精确的TMTV;后者采用图像重建和偏差纠正的方法修正分割未能准确识别的区域,从而进一步提高TMTV的准确性。在芝加哥大学医院的数据集上,该模型的准确率达到71%。与其他方法相比,该模型在TMTV分级方面表现得更加出色。

带式输送机跑偏自动监测系统设计

为有效解决依靠带式输送机传统跑偏保护需要投入的硬件设施数量大、成本高、监测路线长等问题,提出安装固定轨道,采用巡视机器人设备改善皮带监测条件,进而提高检修效率。经实践应用,采用在轨巡视机器人监测技术后,在皮带运行状态监测和跑偏纠错排查方面,每月可缩短检修时间39.5h,将故障率降低到26.6%,人工成本每月节省约4.2万元,具有显著的应用效果。

基于工程量完成形象的水电工程建设投资偏差分析方法研究

水电工程建设通常是在复杂多变的内外部环境条件下进行的,其建设投资管理常常面临较大的风险和挑战。研究贯穿于水电工程建设过程行之有效的事中投资控制理论和方法意义重大。基于工程量完成形象的工程建设投资偏差分析方法在传统赢得值理论基础上进行了拓展创新和有效应用。该方法结合“静态控制、动态管理”投资管理模式,将工程建设投资中的静态部分与动态部分分开,引入“工程量完成形象”的创新概念,关注对工程建设过程中设计工程量的动态跟踪管理,科学合理地确定工程建设过程投资管控目标,重点对已完静态投资进行偏差分析,是一种贯穿于工程建设过程中投资控制管理的有效手段,可广泛适用于国内大多数水电及抽水蓄能工程建设投资管理。文章阐述了改进创新的投资偏差分析方法的理论基础和具体算法,并通过案例展示了实践应用效果。

机器视觉技术在RTG大车自动纠偏系统中的研究与应用

机器视觉技术,在轮胎式龙门起重机行进过程中,实现了对大车的实时偏移量与偏移角度进行的高精度定位检测,进而实现了预测性大车自动纠偏,提高了大车纠偏控制精度。

Metaphor in Imagist Poetry from the Perspective of Stylistics

The imagism is a poetic movement that came out in the 20 th century. In the former period, the poets depend largely on semantic deviation to juxtapose absent and abstract images with readers'familiar and concrete images. In the collision of the images, the readers may sense the beauty of the images and the poets'imagination."Jacobsen points out that the transition from the Modernism to post Modernism is a transition from metaphoric language to metonymic language."(Brooks, 2004) In the later imagist poems, the language becomes metonymic but the uses of metaphor dose not disappear in the poems. The later imagist poets depend on graphological deviation, using language symbols to present the images so as to make the readers feel a different beauty.

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.

A Semi-Vectorial Morphological Segmentation Multi-Component Images of Coumarins on Thin Layer Combined with Laser for Better Separation

In this work, we propose an approach for the separation of coumarins from thin-layer morphological segmentation based on the acquisition of multicomponent images integrating different types of coumarins. The first step is to make a segmentation by region, by thresholding, by contour, etc. of each component of the digital image. Then, we proceeded to the calculations of parameters of the regions such as the color standard deviation, the color entropy, the average color of the pixels, the eccentricity from an algorithm on the matlab software. The mean color values atR = 91.20 in red, atB = 213.21 in blue showed the presence of samidin in the extract. The color entropy values HG = 5.25 in green and HB = 4.04 in blue also show the presence of visnadine in the leaves of Desmodium adscendens. These values are used to consolidate the database of separation and discrimination of the types of coumarins. The relevance of our coumarin separation or coumarin recognition method has been highlighted compared to other methods, such as the one based on the calculation of frontal ratios which cannot discriminate between two coumarins having the same frontal ratio. The robustness of our method is proven with respect to the separation and identification of some coumarins, in particular samidin and anglicine.

不同高度对0°~15°攻角气动光学成像偏移的影响

飞行器在高速飞行过程中,头部产生湍流流场,该流场使机载光学系统接收的目标图像发生偏移、模糊和抖动,这种气体流场对光学传播和光学成像的影响或作用称为气动光学效应。文中研究了典型钝头飞行器在不同高度对0°~15°攻角气动光学成像偏移的影响。使用软件对一种典型的钝头飞行器进行了建模和网格划分,基于计算流体力学使用Fluent作了大量的模拟计算,获得了飞行器不同工况下的周围的流场密度。通过密度和折射率的对应关系,得到了飞行器周围相应的折射率分布。使用反向光线追迹和停止准则,获得了成像偏移数据。结果表明:随着高度的增加,飞行器周围的大气密度减小。尽管不同高度的光线传播路径折射率分布图有着相同的变化趋势,但却有着不一样的变化程度。高度越大,光线传播路径上的折射率分布越平坦,成像偏移越小。从成像偏移斜率来看,随着高度的增加,成像偏移斜率越接近于0;随着攻角的增加,成像偏移斜率在往0的负方向增大。从成像偏移斜率的角度分析,低高度和大攻角都会引起较大的成像偏移值的变化。

基于色貌尺度相位一致性的全参考图像质量评价

为提高图像质量评价模型的准确性,提出一种基于色貌尺度相位一致性的全参考评价模型。首先,在CIELAB色空间的色貌指标Vividness上提取图像结构信息,得到色貌尺度上的相位一致性量值;然后,利用均方根法计算对比度相似图,并在通过上述色空间的颜色通道获取色度相似图;最后,将相位一致性、对比度以及色度三种图像特征结合,采用标准差法进行求和池化,得到全参考图像质量评价计算模型。为验证本模型的可靠性,对4个常用图像数据库中的失真图像进行测试,依据4项评价标准分析其预测精度、计算复杂度及泛化性。实验结果表明,模型在上述数据库中测得的Pearson线性相关系数值最低为0.8781(TID2013),最高达到0.9616(LIVE);Spearman秩相关系数值最低为0.8592(TID2013),最高达到0.9653(LIVE)。与多种现有方法相比,本图像质量评价模型具有更高的视觉关系预测精度。