MRT letter: A total variation based method for 3D shape recovery of microscopic objects through image focus

Generally, shape from focus methods use a single focus measure to compute focus quality and to obtain an initial depth map of an object. However, different focus measures perform differently in diverse conditions. Therefore, it is hard to get accurate 3D shape based on a single focus measure. In this article, we propose a total variation based method for recovering 3D shape of an object by combining multiple depth hypothesis obtained through different focus measures. Improved performance of the proposed method is evaluated by conducting several experiments using images of synthetic and real microscopic objects. Comparative analysis demonstrates the effectiveness of the proposed approach. Microsc. Res. Tech. 76:877–881, 2013. © 2013 Wiley Periodicals, Inc.     

Shape from focus based on 3D structure tensor using optical microscopy

Shape from focus (SFF) is a widely used passive optical method for 3D shape reconstruction. In SFF, a focus measure, which is used to estimate the relative focus level, plays a critical role in depth estimation. In this article, we present a new focus measure for accurate 3D shape estimation in optical microscopy based on the analysis of 3D structure tensor. First, the 3D tensors are computed from the input image sequence for each pixel. Then, each tensor is decomposed into point, curve, and surface tensors by decomposing tensors into eigenvalues and eigenvectors. Finally, the surfaceness is used to measure the quality of sharpness. The proposed focus measure provides accurate focus values and better resistance against noise. The proposed measure is evaluated by conducting experiments using image sequences of simulated and microscopic real objects. The comparative analysis demonstrates the effectiveness of the proposed focus measure in recovering 3D shape.     

A novel method for shape from focus in microscopy using Bezier surface approximation

In this article, we introduce a novel shape from focus method to compute 3D shape of microscopic objects, based on modified‐pixel intensities and Bezier surface approximations. A new and simple but effective focus measure is proposed. In our focus measure, the original intensities of a sequence of small neighborhood are modified by subtracting the maximum of the values of first and last frames. An initial depth map is calculated by finding the maximum of the pixel's focused energy and its corresponding frame number. Missing information between two consecutive frames, false depth detection, and enhancement of noise related intensities may provide inaccurate depth map. To overcome these problems and to produce an accurate depth map, we proposed Bezier surface approximation. The proposed method is tested using synthetic and real image sequences. The comparative analysis demonstrates the effectiveness of the proposed method. Microsc. Res. Tech., 2010. © 2009 Wiley‐Liss, Inc.     

Searching surface orientation of microscopic objects for accurate 3D shape recovery

In this article, we propose a new shape from focus (SFF) method to estimate 3D shape of microscopic objects using surface orientation cue of each object patch. Most of the SFF algorithms compute the focus value of a pixel from the information of neighboring pixels lying on the same image frame based on an assumption that the small object patch corresponding to the small neighborhood of a pixel is a plane parallel to the focal plane. However, this assumption fails in the optics with limited depth of field where the neighboring pixels of an image have different degree of focus. To overcome this problem, we try to search the surface orientation of the small object patch corresponding to each pixel in the image sequence. Searching of the surface orientation is done indirectly by principal component analysis. Then, the focus value of each pixel is computed from the neighboring pixels lying on the surface perpendicular to the corresponding surface orientation. Experimental results on synthetic and real microscopic objects show that the proposed method produces more accurate 3D shape in comparison to the existing techniques.     

Multidirectional focus measure for accurate three-dimensional shape recovery of microscopic objects

Shape from focus (SFF) is a technique to recover the shape of an object from multiple images taken at various focus settings. Most of conventional SFF techniques compute focus value of a pixel by applying one of focus measure operators on neighboring pixels on the same image frame. However, in the optics with limited depth of field, neighboring pixels of an image have different degree of focus for curved objects, thus the computed focus value does not reflect the accurate focus level of the pixel. Ideally, an accurate focus value of a pixel needs to be measured from the neighboring pixels lying on tangential plane of the pixel in image space. In this article, a tangential plane on each pixel location (i, j) in image sensor is searched by selecting one of five candidate planes based on the assumption that the maximum variance of focus values along the optical axis is achieved from the neighborhood lying on tangential plane of the pixel (i, j). Then, a focus measure operator is applied on neighboring pixels lying on the searched plane. The experimental results on both the synthetic and real microscopic objects show the proposed method produces more accurate three-dimensional shape in comparison to conventional SFF method that applies focus measures on original image planes.     

PCA-based method for 3D shape recovery of microscopic objects from image focus using discrete cosine transform

This article introduces a new algorithm for shape from focus (SFF) based on discrete cosine transform (DCT) and principal component analysis (PCA). DCT is applied on a small 3D neighborhood for each pixel in the image volume. Instead of summing all focus values in a window, AC parts of DCT are collected and then PCA is applied to transform this data into eigenspace. The first feature, containing maximum variation is employed to compute the depth. DCT and PCA are computationally intensive; however, the reduced data elements and algorithm iterations have made the new approach competitive and efficient. The performance of the proposed approach is compared with other methods by conducting experiments using image sequences of a synthetic and two microscopic objects. The evaluation is gauged on the basis of unimodality, monotonicity, and resolution of the focus curve. Two other global statistical metrics, root mean square error (RMSE) and correlation have also been applied for synthetic image sequence. Besides, noise sensitivity and computational complexity are also compared with other algorithms. Experimental results demonstrate the effectiveness and the robustness of the new method.     

MRT Letter: Guided filtering of image focus volume for 3D shape recovery of microscopic objects

In this letter, a shape from focus (SFF) method is proposed that utilizes the guided image filtering to enhance the image focus volume efficiently. First, image focus volume is computed using a conventional focus measure. Then each layer of image focus volume is filtered using guided filtering. In this work, the all‐in‐focus image, which can be obtained from the initial focus volume, is used as guidance image. Finally, improved depth map is obtained from the filtered image focus volume by maximizing the focus measure along the optical axis. The proposed SFF method is efficient and provides better depth maps. The improved performance is highlighted by conducting several experiments using image sequences of simulated and real microscopic objects. The comparative analysis demonstrates the effectiveness of the proposed SFF method. Microsc. Res. Tech. 77:959–963, 2014. © 2014 Wiley Periodicals, Inc.     

基于双拟合优化的聚焦深度三维形貌测量方法

聚焦深度法广泛地应用于小尺寸零构件的三维形貌测量。 针对聚焦评价曲线多存在噪声导致三维形貌测量的精度下 降,且效率受图像序列数目和聚焦评价算法限制的难题,通过结合双拟合优化理论与聚焦单峰性评价指标提出了一种基于自适 应权重的聚焦极值搜寻方法,并进一步基于三次多项式二次插值算法和多级中值混合滤波优化深度信息。 实验结果表明,方法 对仿真图像数据的均方根误差(RMSE)较高斯拟合和多项式拟合分别降低了 19. 08% 、17. 32% , 对球栅阵列封装 (BGA) 图像 中受噪声干扰较大的区域仍具三维分辨能力,同时对钻削刀具进行了测量,提出的方法在 50% 的图像序列数目和图像分辨下 RMSE 仍降低了 77. 8% 、62. 6% ,有效减少了聚焦曲线噪声对测量结果影响的同时提升了三维测量的效率。     

MRT Letter: Optimal composite depth function for 3D shape recovery of microscopic objects

Generally, in shape from focus techniques, a single focus measure is used in estimating the three‐dimensional structure of microscopic objects. However, the performance of a single focus measure is limited to estimate accurately the depth map of diverse type of objects. To cope with this problem, we propose genetic programming based novel approach by developing an optimal composite depth (OCD) function for accurate depth estimation. This OCD function optimally combines the initial depth and focus information extracted from individual focus measures. An improved performance of this function is reported for synthetic and real world microscopic objects. Microsc. Res. Tech., 2010. © 2010 Wiley‐Liss, Inc.     

Inspection of weld shape based on the shape from shading

The weld bead shape is crucial for weld quality. Automatic inspection on the 3D shape of a weld bead is achieved by recording the image of the weld bead with an optical sensing method and then calculating the 3D shape parameters with a shape-from-shading technology based on a single image in the computer-vision domain. The paper first introduces a method of shape from shading based on a single image and puts forward its implementation. It then presents the improved measures of the original algorithm according to the defects of the computed results and finds accuracy compared with the former method by a synthetic image. Finally, the improved algorithm is applied to the surface height reconstruction of weld bead successfully .     

基于单目视觉的自由曲面三维坐标测量方法

本文将单摄像机与三坐标测量机结合设计了一种自由曲面的三维坐标测量方法.自由曲面的表面经坐标测量机带动摄像机序列采集图像后形成图像体积,然后使用调焦评价函数在图像体积内寻优判断,找到自由曲面的正焦图像表面.根据物像关系式和正焦图像表面即可推得自由曲面点的三维坐标.经实验比较,本系统测量结果与接触式坐标测量机测量曲面点Z坐标极限偏差13 μm.     

基于小波分析的显微序列图像合成系统

由于显微镜物镜焦深范围有限,故造成显微图像局部模糊,研究人员对图像的理解不完整等问题。根据聚焦评价函数分布,采用小波分析,将一序列局部聚焦图像合成全焦图像。改进的小波融合算法得到的融合图像极大地保留了系列图像聚焦部分的信息,合成全焦图像。由此得出的聚焦合成图像使研究人员可直接测量所需的显微结果。     

反求工程中基于图像的汽车零部件曲面的重建

从明暗恢复形状是计算机视觉中的一个重要的研究课题,其目的是利用单幅图像中明暗变化等信息来恢复其表面形状.本文提出的是一种基于汽车零部件曲面图像的三维数据模型重建方法,根据从明暗恢复形状原理实现汽车零部件灰度图像的深度信息提取,通过可视化编程实现建模过程.     

Improving focus measurements using logarithmic image processing

The logarithmic image processing (LIP) model is a mathematical framework which provides algebraic and functional operations for the processing of intensity images valued in a bounded range. The LIP model has been proved to be physically consistent, most notably with some image formation models and several laws and characteristics of human brightness perception. This paper addresses the image focus measurement problem using the LIP model. The three most classical image focus measurements: the sum-modified-Laplacian, the tenengrad and the variance, which aim at estimating the degree of focus of an acquired image by emphasizing and quantifying its sharpness information, are considered and reinterpreted using the LIP framework. These reinterpretations notably make attempts at evaluating degrees of focus in terms of human brightness (sensation) from physical light stimuli. Their potential is illustrated and validated on shape-from-focus issues on both simulated data and real acquisitions in digital optical microscopy. The concept of shape-from-focus involves recovering the shape of an observed thick sample by locally maximizing a focus measurement throughout a sequence of differently focused images. Finally, it is shown that the LIP-based focus measurements clearly outperform their respective classical ones.     

一种基于DFD的自动对焦算法

引入了一种基于DFD的自动对焦算法。通过这种算法,只要给定了两幅不同离焦位置的图像,就可由算法推导出目标物体的正确对焦位置,从而控制镜头完成自动对焦。实验表明,这种算法精度比较高,速度比较快,鲁棒性良好。     

基于明暗恢复形状的加工表面形貌重构与粗糙度检测

研究了采用明暗恢复形状法(SFS)对加工表面显微视觉图像的三维形貌重构,并实现了表面粗糙度检测.根据金属表面反射特性,采用简化的Oren-Nayar模型与Torrance-Sparrow模型中镜面反射分量叠加的方法,对光照模型进行了改进,并讨论了基于改进后光照模型的SFS最小化计算方法.利用该算法,实现了真实工件表面微...     

一种基于SFS方法的含高光表面三维重构系统

针对含高光表面三维形状重构的需求,设计了一种基于从明暗恢复形状(SFS)方法的三维重构系统。在正交投影条件下由CCD相机获取点光源照射下的物体表面图像,使用Ward反射模型描述含高光表面的反射特性,建立物体表面图像辐照度方程。系统软件将该方程转化为包含物体高度信息的H-J偏微分方程,并计算此偏微分方程的解,得到物体的高度函数,进而恢复出物体的表面形状。实验表明,该系统可以有效地重构含高光表面的三维形状。     

基于位相检测的光学三维轮廓测量方法

三维轮廓测量是当前光学研究领域中非常活跃的一个技术分支,其中位相测量轮廓术(PMP)在求解中严格遵循物像共轭关系,具有较高的测量精度。DMD器件的出现,更推进了PMP技术的发展。本文重点讨论了位相测量轮廓术(PMP)测量中的典型问题,介绍了PMP的应用现状。