An image mosaic technique with non-overlapping regions based on microscopic vision in precision assembly

Microscopic vision has been widely applied in precision assembly.To achieve sufficiently high resolution in measurements for precision assembly when the sizes of the parts involved exceed the field of view of the vision system,an image mosaic technique must be used.In this paper,a method for constructing an image mosaic with non-overlapping areas with enhanced efficiency is proposed.First,an image mosaic model for the part is created using a geometric model of the measurement system installed on a X-Y-Z precision stages with high repeatability,and a path for image acquisition is established.Second,images are captured along the same path for a specified calibration plate,and an entire image is formed based on the given model.The measurement results obtained from the specified calibration plate are utilized to identify mosaic errors and apply compensation for the part requiring measurement.Experimental results show that the maximum error is less than 4μm for a camera with pixel equivalent 2.46μm,thereby demonstrating the accuracy of the proposed method.This image mosaic technique with non-overlapping regions can simplify image acquisition and reduce the workload involved in constructing an image mosaic.

Classification of African Mosaic Virus Infected Cassava Leaves by the Use of Multi-Spectral Imaging

In this work, we have used multispectral imaging technology to classify cassava leaves infected by African mosaic virus by the use of their unique spectral finger print. The spectra are extracted from transmission, reflection and diffusion of their multispectral images;they have been then analyzed with statistical multivariate analysis techniques. Principal component analysis (PCA) has been used followed by K-means and Ascending Hierarchical Classification (AHC) to endorse the classification. The contribution of this work is the use of multispectral imagery which binds both spatial and spectral information to differentiate and sort infected leaves. The results show that the multimodal and imaging spectroscopy may allow blind identification and characterization of infected leaves.

A novel method for eliminating rotation deviation in sequential images mosaic

To eliminate rotation deviation of sequential images mosaic when measuring linear dimensions of large scale parts with computer vision, a novel algorithm based on the chain code searching method is proposed. After image preprocessing, including image filtering, image segmentation, and edge detection, the chain code length of the contour line can be searched out by the proposed method. Then, the angle from the contour line to the coordinate axis is computed with the length of the contour line. After that, the sequence is rotated in the opposite direction and the rotation deviation is eliminated. It is prepared for the next mosaic of sequences in eliminating shifting deviation. Experiments are carried out on parts with a linear profile rotating angle from 0° to 9°. The results show that compared with the commonly used Hough transform, the new method has higher precision and faster speed, which is important in realizing online high precision measurements of large scale parts with a linear profile.

Bionic Mosaic Method of Panoramic Image Based on Compound Eye of Fly

To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this system to imitate the small eyes of a compound eye. Based on the optical analysis of this system, a direct panoramic image mosaic algorithm was proposed. Several sub-images were collected by the bionic compound eye visual system, and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images. Thus, a panoramic image with a large field of view was directly mosaicked, which expanded the field and guaranteed the high resolution. The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality. Furthermore, the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors. This method has better real-time properties compared to other methods.

Modified SIFT descriptor and key-point matching for fast and robust image mosaic

To improve the performance of the scale invariant feature transform （ SIFT）, a modified SIFT （M-SIFT） descriptor is proposed to realize fast and robust key-point extraction and matching. In descriptor generation, 3 rotation-invariant concentric-ring grids around the key-point location are used instead of 16 square grids used in the original SIFT. Then, 10 orientations are accumulated for each grid, which results in a 30-dimension descriptor. In descriptor matching, rough rejection mismatches is proposed based on the difference of grey information between matching points. The per- formance of the proposed method is tested for image mosaic on simulated and real-worid images. Experimental results show that the M-SIFT descriptor inherits the SIFT＇ s ability of being invariant to image scale and rotation, illumination change and affine distortion. Besides the time cost of feature extraction is reduced by 50% compared with the original SIFT. And the rough rejection mismatches can reject at least 70% of mismatches. The results also demonstrate that the performance of the pro- posed M-SIFT method is superior to other improved SIFT methods in speed and robustness.

A Mosaic Technique Based on Image Registration

osaic technique and image registration process are studied in this paper. By image registration, the correspondence between images of the same scene can be established. The aim of mosaic is to build up the scene panorama of a real image sequence of the same scene. So mosaic can be integrated by way of image registration. Here, some image registration method is given, and then affine transformation is taken. Finally, the image sequence is built into the panorama.

Slicing Method for Reverse Engineering Based on Image Mosaic

Reverse engineering dealing with images is traditionally based on image processing and contour recognition. A new method is presented based on the combination of sectional slicing with image mosaic. Sectional contours of the target object are generated by colorful liquid or laser scanning, these images from different views are fused into a set of complete cross-sectional images, thereby the whole practical model is reconstructed in 3D space.

A Fast Algorithm for Automated Image Mosaicing

This paper presents a fast image mosaic algorithm based on the characteristic of the edge grads. Unlike some previous algorithms, which require pure horizontal camera panning, this algorithm doesn＇t require constraints on how the image is taken. The algorithm can determine the matching regions of the two adjacent images by finding out the feature points and can piece up images bath horizontally and vertically. Experimental results show that this algorithm is effective.

A Real Time Mosaic Method for Remote Sensing Video Images from UAV

At present, in order to get a large field of view image, image mosaic technique has been widely applied in UAV remote sensing platform. The traditional mosaic system for UAV remote sensing image takes a lot of time and man power, it is difficult to complete the image stitching automatically. In the paper, an approach for geometric correction of remote sensing image without any ground control points is presented, and the SIFT algorithm is used to extract and match feature points. Finally, the weighted average fusion method is used to smooth the image after splicing and an automatic mosaic system for UAV remote sensing video images is developed. In order to verify the system, some splicing ex-periments using UAV actual aerial photography images have been done and good results have been achieved.

Image Mosaic Techniques Optimization Using Wavelet

This essay concentrates on two key procedures of image mosaic--image registration and imagefusion.Becauseof the character of geometric transformation invariance of edge points, wecalculate the angle difference of the direction vector ofedge points in different images anddraw an angle difference histogramto adjust the rotationproblem. Through this way, algorithm based on gray information is expandedandcan be used in images withdisplacementand rotation. Inthe term of image fusion, wavelet multi-scale analysis is used to fuse spliced images. In order to choose the best method of imagefusion,weevaluate the results of different methods of image fusion by cross entropy.

Mosaic of the Curved Human Retinal Images Based on the Scale-Invariant Feature Transform

To meet the needs in the fundus examination,including outlook widening,pathology tracking,etc.,this paper describes a robust feature-based method for fully-automatic mosaic of the curved human retinal images photographed by a fundus microscope. The kernel of this new algorithm is the scale-,rotation-and illumination-invariant interest point detector & feature descriptor-Scale-Invariant Feature Transform. When matched interest points according to second-nearest-neighbor strategy,the parameters of the model are estimated using the correct matches of the interest points,extracted by a new inlier identification scheme based on Sampson distance from putative sets. In order to preserve image features,bilinear warping and multi-band blending techniques are used to create panoramic retinal images. Experiments show that the proposed method works well with rejection error in 0.3 pixels,even for those cases where the retinal images without discernable vascular structure in contrast to the state-of-the-art algorithms.

基于改进SIFT算法的超声图像拼接方法

针对大型结构超声C扫描获得的多幅子图像,为了获取被测结构的全景图像,研究图像的拼接方法.根据超声波法成像检测的动态过程并结合数字化图像处理技术,在传统的基于尺度不变特征变换(scale invariant feature transform,SIFT)算法基础上,提出了一种改进的超声C扫描检测图像拼接方法.首先,针对传统SIFT算法存在超声图像配准成功率低的问题,利用超声扫查过程中探头起始位置的矢量差对SIFT算法得到的特征点粗匹配结果进行筛选;其次,采用动态规划的方法寻找最佳缝合路径;最后,沿最佳缝合路径进行渐入渐出融合以改善融合区域的视觉效果.人工缺陷试块及焊接结构试件超声图像的拼接结果表明,基于改进的SIFT图像拼接算法可以将多幅超声C扫描子图像有效拼接为全景图像;所提方法特征点匹配准确率高、图像融合失真小,优于常规SIFT图像拼接算法;拼接图像中,目标位置关系对应良好,可实现结构加工质量的整体无损评价.

基于双目视觉的柔性塑胶套壁厚检测系统研究

为了完成锥形波纹管形状的柔性塑胶防尘套壁厚的检测,建立一个基于双目立体视觉模型的测量系统。该系统中的两个工业数字摄像机通过PLC给予的外触发对工件同时进行图像采集,对采集的多组图像进行相应的预处理后,采用特征点提取方法实现图像拼接,运用特征匹配算法提取出相应待测点三维坐标信息,完成柔性塑胶防尘套壁厚检测。该测量系统,使用气动柔性夹爪夹取工件,减少柔性工件的夹取变形影响,使用高精度移动滑台带动工件运动到拍照位置,通过控制滑台特定的移动距离和对图形特征提取结合方法对多次拍照后的工件图像进行特征点筛选和图像拼接,完成工件壁厚的高精度检测。实验数据表明,该测量系统绝对检测精度达±0.05mm以内,简单快捷,缩短了工件生产工作中的设备调整时间。

多矢量姿态测量算法研究综述

将矢量测量转化为姿态测量,该问题在姿态估计中被称为Wahba问题。介绍了最小化Wahba问题的损失函数的不同算法,包括最优四元数估计器(ESOQ)、四元数估计器(QUEST)、快速最优姿态矩阵(FOAM)、矩阵的奇异值分解(SVD)等广泛使用的算法,以及基于快速线性四元数姿态估计器(FLAE)、黎曼流形等近年来提出的算法。给出了简单的计算原理与推导过程,并通过计算机仿真对照,归纳各类算法在计算旋转矩阵时的计算精度、鲁棒性。针对姿态测量算法应对当前应用场景的性能需求,简要介绍其在惯性测量单元(IMU)动态对准、协同集群视觉定姿、图像拼接等方面的适用可能和工作原理,并在此基础上简述了姿态测量算法当前的缺陷与未来的发展趋势。

基于匹配的车载环视图像拼接标定研究

车载环视系统是辅助安全驾驶、消除车身四周盲区的重要有效装备,为改善图像拼接标定的精度及实现自动标定,设计图像拼接标定板,提出形状匹配的标定方法。标定板采用圆形图案并按矩形及对角五点布局方式,适用于“F-B-L-R”和“F-B-L-R-Z-Y”及多节牵引挂车场合,基于形状匹配的算法融合最小二乘法、图像金字塔及模板预训练的方法,实现了图像拼接标定。仿真实验表明,标定板具有良好的鲁棒性、算法具有良好的标定精度,能够实现自动化标定。

利用正射影像立体像对的无人机测图系统

利用无人机影像通过传统立体像对模型测图时需要频繁切换像对,将无人机影像制作为实景三维模型测图时则需频繁平移、缩放和旋转模型,两种方式都存在效率低的问题。正射影像立体像对可将成百上千个立体像对的左右片各自无缝拼接起来,形成覆盖超大范围的立体像对。开发了基于正射影像立体像对的无人机测图系统,作业模式与传统立体像对相似,但避免了像对切换,提高了作业效率。在多个项目中开展了1∶2000测图实验,该系统平面精度约为0.2 m,高程精度为0.2~0.4 m。

基于分类配准与全景像素坐标系的显微图像快速拼接算法

目的提出一种基于分类配准与全景像素坐标系的显微图像实时拼接算法,以解决现有图像拼接算法精度低、计算复杂度高等问题。方法依据单视野图像的质量特征,利用评价函数对图像进行分类配准,适应不同的配准模型;构建全景像素坐标系,依据配准结果在此坐标系下进行整体拼接与缝隙融合;基于自主搭建的尿液样本显微扫描系统进行实验,以验证算法的有效性。结果实验结果表明,相比现有的图像拼接方法,本文基于分类配准与全景像素坐标系的显微图像快速拼接算法更有利于拼接缝隙的融合,且更稳定,拼接效果显著优于加速鲁棒特征和快速傅里叶变换单独拼接;在拼接时间方面,基于分类配准与全景像素坐标系的显微图像实时拼接算法的拼接时间大大缩短,拼接速度提升了1倍,且对于矩形扫描区域拼接的大视野图像,无明显拼接缝隙痕迹,可完成高质量的实时拼接。结论基于分类配准与全景像素坐标系的显微图像快速拼接算法能够满足快速高分辨率的大视野图像拼接需求,为显微图像拼接提供了一种更优的方法,便于相关人员进一步分析和应用。

基于ERDAS IMAGINE的扫描地形图的处理方法

阐述了扫描地形图的处理方法,对技术流程的关键问题作了详细的说明。解决了如何在控制误差精度的情况下,将单幅图像拼接成整幅地形图时的校正、裁剪、拼接等问题,总结探讨了在ER-DAS IMAGINE 8.6中利用地面控制点对扫描地形图进行的几何校正、拼接等处理方法,并对成果进行了精度分析。

一种基于FPGA的实时图像拼接融合算法电路设计

图像拼接在全景等领域应用广泛,其关键技术包括图像配准和图像融合两个部分。为了达到低成本和实时处理,往往需要研究图像拼接电路设计,但众多研究集中于图像配准算法,忽视图像融合算法,更不用说专用电路设计。图像配准算法电路以及外设控制器电路由于其复杂性通常会消耗电路中绝大部分资源,因此,图像融合电路的性能和资源利用就成为影响图像拼接系统性能的两个关键因素。为了高效且低资源消耗地实现配准后图像的融合,设计了一种基于贪心算法搜索接缝线的图像融合算法电路,搭建了完整的从图像数据输入到显示输出的验证原型系统。基于Cyclone IV现场可编辑门阵列(Field Programmable Gate Array,FPGA)器件的综合结果和理论分析表明,提出的电路在保持低资源占用率和显示效果的同时在时钟频率100 MHz下完成两幅486×643的图像融合耗时6.5795 ms,约为144 FPS,达到了实时性要求,且经过理论换算,处理速率优于3个比较对象。