A fast auto-focusing method of microscopic imaging based on an improved MCS algorithm

An improved"three steps"mountain-climb searching(MCS)algorithm is proposed which is applied to auto-focusing for microscopic imaging accurately and efficiently.By analyzing the performance of several evaluation functions,the variance function and the Brenner function are synthesized as a new evaluation function.In the first step,a self-adaptive step length which is much dependent on the reciprocal of the evaluation function value at the beginning position of climbing is used for approaching the halfway up the mountain roughly.Secondly,a fixed moderate step length is applied for approaching the mountaintop of the variance function as closer as possible.Finally,afine step is employed for reaching the exact mountaintop of the Brenner function.The microscope auto-focusing experiments based on the proposed algorithm for blood smear detection have been carried out comprehensively.The results show that the improved algorithm can not only guarantee the precision to get clear focal images,but also improve the auto-focusing e±ciency.

Real-time auto-focusing technique using centroid method for space camera

A real-time auto-focusing system with auto-collimation method is introduced, which is used in auto-detecting the focus of the space camera with long focus. Auto-focusing is the key technique to ensure high quality in space imaging. It can measure and compensate the defocus caused by the change of temperature and air pressure etc. in space. To solve the problem of auto-focusing with auto-collimation method of the camera whose axis is perpendicular to the ground, it is designed that two small caliber pentagonal prisms are placed in the area of aperture suitable to the camera’s relative aperture based on the theory of auto-focusing with auto-collimation, which can replace the big caliber plane reflector used in other cameras. Using the characteristic of pentagonal prism refracting light vertically, the target slit is imaged in CCD through the two-separated lens. It transforms the detecting of the axial defocusing quantity to the landscape orientation measurement of the faculae’s position in the direction of CCD pixels. The defocusing quantity is obtained by measuring the opposite position of the two faculae on the CCD. The Centroid method is adopted to measure the position of the auto-collimation faculae. The arithmetic error is analyzed especially, and the causation is given. Experiments show that this real-time auto-focusing system using centroid method is reliable and the focusing precision can reach ±0.01 mm.

3D Surface Morphology Measurement and Auto-focusing System

When interference microscope measures the surface rough of the micromechanical device, as soon as the work distance of interference microscope and the depth of field is shortened, the interference images become slur for the measured object if there has small interference after clear focus. The auto-focusing system is introduced into the interference microscope, the system can obtain high definition interference image rapidly,and can improve the measuring velocity and measuring precision. The system is characterized by auto-focusing range of ±150 μm, auto-focusing precision of ±0.3 μm, auto-focusing time of 4～8 s.

Integrated lens auto-focus system driven by a nut-type ultrosonic motor (USM)

This paper introduces an integrated optical auto-focus system driven by a nut-type ultrasonic motor (USM). The system comprises an optical lens as a rotor (M6 or M7), a polyhedral tube of copper as a stator; an image sensor, and a driver IC of the motor. The sizes of the AF (auto-focus) module are 8.5 mm×8.5 mm×5.9 mm. The piezoelectric elements are bonded on the external surface of the stator. The rotor has external screw thread that engages with the inner screw thread of the stator. When the piezoelectric elements are excited by the driver IC, a bend traveling wave in plane is generated on the stator along the circle direction, that drives the lens rotor to rotate and then to move axially. The driver IC is controlled by an image feedback of an image sensor centered on the axis of the casing, then the optical focusing is realized. The power consumption is zero at rest and is less than 0.25 W in motion; focusing precision <10 μm; speed >3 r/s(180 r/min); response <10 ms; high reliability: resistant to shock and fall off; directly driven by the driver IC without transmission mechanism; the friction force is namely the driving force and noiseless. The integrated optical auto-focus system is very useful, especially for cellular phones. The image resolution of 3―5 MP has been obtained in the module prototypes of the cellular phone.

A fast face detection architecture for auto-focus in smart-phones and digital cameras

Auto-focus is very important for capturing sharp human face centered images in digital and smart phone cameras. With the development of image sensor technology, these cameras support more and more highresolution images to be processed. Currently it is difficult to support fast auto-focus at low power consumption on high-resolution images. This work proposes an efficient architecture for an Ada Boost-based face-priority auto-focus. The architecture supports block-based integral image computation to improve the processing speed on high-resolution images; meanwhile, it is reconfigurable so that it enables the sub-window adaptive cascade classification, which greatly improves the processing speed and reduces power consumption. Experimental results show that 96% detection rate in average and 58 fps(frame per second) detection speed are achieved for the1080p(1920×1080) images. Compared with the state-of-the-art work, the detection speed is greatly improved and power consumption is largely reduced.

针对不停机风力发电机改进的自动调焦系统

风能是一种重要的可再生资源,因此对风力发电机组进行损伤检测具有重要意义。由于叶片图像的清晰度对损伤检测有很大影响,因此需要通过自动调焦步骤获得清晰的图像。不停机风力发电机叶片追踪图像中叶片的位置和尺寸改变,无法准确评估图像清晰度。因此,通过聚焦搜索策略无法实现自动聚焦步骤。文中提出一种基于改进的清晰度评价方法的自动调焦系统。通过基于面积补偿系数的方法补偿清晰度评价,并进行仿真实验和风力发电机模型实验。叶片目标变化对清晰度评价的影响从0.218降至0.030,叶片目标变化对清晰度的影响大大降低。在改进的清晰度评价方法的基础上,采用爬山法的搜索策略实现自动调焦步骤,同时,由于需要考虑算法程序对于不停机风力发电机的实时性,计算了自动调焦步骤的消耗时间,通过降低图像分辨率和调用NumPy库,将耗时从13.79 s减小到0.1 s以下。最后,实现了不停机风力发电机叶片追踪图像的自动调焦步骤,为提高自动调焦技术的性能提供了借鉴。

用于影像测量仪垂直尺寸测量的自动对焦技术

影像测量仪垂直尺寸测量的自动对焦精度越高,垂直尺寸测量误差就越小。通过对清晰度评价函数性能指标的比较,选择了改进的Tenengrad梯度评价函数;对焦窗口选择全窗口;提出粗精结合的搜索策略,粗对焦时,使用结合二分法的爬山搜索算法;精对焦时,使用结合全局搜索算法的高斯曲线拟合法。实验结果表明:自动对焦算法鲁棒性良好,对焦精度高,可达到5μm(1/20景深),平均对焦时间为10 s,能满足实时性要求。

图像清晰度评价与变步长融合调焦方法

十字丝目标在CCD上的成像,一般受到环境光和光路的影响,不同位置的焦距产生的十字丝图像会存在边缘模糊和离焦的情况,使十字目标的中心点位置提取受到严重影响,传统的Sobel算法忽视边缘信息,并且容易受噪声影响,因此提出改进Sobel算子图像清晰度评价函数与粗细调焦结合的变步长两段式快速搜索自动调焦的方法。该方法首先利用图像的空间域评价图像清晰度,其次利用根据光学设计选用的两段式调焦方式。第一步进行粗调,先快速找到正焦位置附近,然后进行细调,直至找到正焦的位置。实验表明,该方法与其他算法相比,自动调焦失败率为2%,调焦时间为1 242 ms,调焦行程在-25~+30 mm之间。通过该算法将图像清晰度评价函数与两段式调焦方式结合进行自动调焦,准确性高,实时性好。

Entropy function optimization for radar imaging

The convergence performance of the minimum entropy auto-focusing（MEA） algorithm for inverse synthetic aperture radar（ISAR） imaging is analyzed by simulation. The results show that a local optimal solution problem exists in the MEA algorithm. The cost function of the MEA algorithm is not a downward-convex function of multidimensional phases to be compensated. Only when the initial values of the compensated phases are chosen to be near the global minimal point of the entropy function, the MEA algorithm can converge to a global optimal solution. To study the optimal solution problem of the MEA algorithm, a new scheme of entropy function optimization for radar imaging is presented. First, the initial values of the compensated phases are estimated by using the modified Doppler centroid tracking （DCT）algorithm. Since these values are obtained according to the maximum likelihood （ML） principle, the initial phases can be located near the optimal solution values. Then, a fast MEA algorithm is used for the local searching process and the global optimal solution can be obtained. The simulation results show that this scheme can realize the global optimization of the MEA algorithm and can avoid the selection and adjustment of parameters such as iteration step lengths, threshold values, etc.

基于区域对比度的图像清晰度评价算法

高效、准确的图像清晰度评价是实现自动调焦的关键。在分析了现有图像清晰度评价方法优缺点的基础上,提出了一种基于图像区域对比度的清晰度评价新方法,建立和分析了评价函数的数学模型,并对航空摄像机采集的系列图像进行实验和仿真。与其他算法比较的结果表明:该方法具有精确度高、对比度明显等优点,能够应用于实际的图像清晰度评价和自动对焦中,克服了单纯依靠计算灰度差带来的不足,具有较高的实用性和可靠性。

基于图像处理的微装配自动调焦系统

介绍了一个基于图像处理的自动调焦系统,该系统由光学显微镜、CCD、力矩电机和齿轮传动机构等组成。调焦系统中采用粗/精结合的调焦方法,即首先采用基于Krisch边缘检测算子的清晰度评价函数对被测物体进行粗调焦,并在计算机上采集了包含目标的大致轮廓和边缘的显微图像;然后针对全景图像上的某个目标区域采用基于高频分量的清晰度评价函数进行精调焦,使得显微图像显示出更多的纹理细节。实验中清晰度评价函数算法均采用Windows下的Visual C++实现。实验结果表明,该自动调焦的系统精度可达±4.8μm,基本上满足了微装配任务的调焦精度要求。

一种新的图像清晰度评价函数

离焦模糊图像清晰度评价函数是采用数字图像处理技术实现自动调焦的一个关键,需要不断地提高评价函数的准确性和有效性。深入研究了各种图像梯度的分布情况后发现模糊图像小梯度像素数较大,而清晰图像大梯度的像素数则明显比模糊图像的多,因此可以给梯度加一个阈值,去掉梯度小的值保留梯度大的值,这样可以突出清晰图像的的优势,易于准确判断。首次提出了一种用图像梯度加阈值求和作为由于离焦产生的模糊图像的评价函数,建立了上述评价函数的数学模型,并给出了实验结果和分析。与以往的图像灰度方差、梯度和、小波变换等评价函数相比,给出的评价函数无偏性好、单峰性强,信噪比高,计算量小,在焦平面附近具有变化趋势明显和灵敏度高的特点。

基于全自动控制显微镜的自动聚焦算法研究

图像自动聚焦评价函数的选择是全自动控制显微镜无源方式自动聚焦系统的关键问题。对几种主要的图像聚焦评价函数 (灰度方差算子、灰度梯度算子、能量谱方法等 )进行了比较、研究 ,并在此基础上首次将改进的 L aplacian算子作为聚焦评价函数引入自动聚焦之中 ,同时为了消除噪声的影响 ,引入了步长和阈值两个参数。实验结果表明 ,改进的L aplacian算子比其他评价函数更为准确、稳定和可靠 。

基于Roberts梯度的自动聚焦算法

如何快速有效地实现聚焦一直是图像测量中的焦点,其中图像自动聚焦评价函数的选择是关键问题。在比较、研究图像聚焦评价函数和边缘检测的基础上,提出了将Roberts梯度算子作为聚焦评价函数引入自动聚焦之中,同时为了消除噪声的影响,仔细研究阈值问题,并引入了一个阈值参数。经过大量的仿真实验,画出了几种自动聚焦算法的聚焦图形,并进行了详细的比较分析。结果表明,引入参数的Roberts算子具有无偏性好、单峰性强、灵敏度高等特点,该算子比其他评价函数更为准确、稳定、可靠。

显微视觉系统中自动聚焦技术的研究

在聚焦评价算法的研究中,本文首先对传统的离散余弦变换(DCT)算法和最小核值相似区(SUSAN)算法进行改进,然后结合改进后的DCT算法和SUSAN算法提出一种新的聚焦评价算法,该算法结合频域评价算法和空间域评价算法各自的优点,使聚焦曲线在单峰性,局部极值点和灵敏度等方面与传统算法相比有较大改善。在聚焦窗口的研究中,本文提出一种基于图像子块重要程度加权的聚焦窗口选择方法,该方法以总梯度变化率作为图像子块重要程度因子,将重要程度因子值小于阈值的图像子块视为背景子块,去除背景子块后剩下的部分为聚焦窗口。新的聚焦窗口选择方法能实现动态的区分目标区域与背景区域。

基于加权邻域相关性的显微镜自动聚焦函数

提出了一种基于加权邻域相关性的显微镜自动聚焦函数，并在研究显微镜聚焦原理及成像过程的基础上，分析了显微镜图像中像素邻域灰度相关性及像散现象对聚焦评价的影响。首先，分别计算每幅显微镜序列图像中各像素与其四邻域像素的灰度相关性。然后，计算基于此相关性加权平均值的二次多项式聚焦函数，其中的权值则根据对应像素与显微镜视场中心的距离来确定。最后，选取该函数值最大的图像为聚焦图像。实验结果表明，与经典的聚焦函数（如方差函数、绝对梯度函数、Roberts梯度函数及Tenengrad函数）相比，本文方法的聚焦灵敏度因子提高了0．3185～0．3268，噪声环境下聚焦的平均正确率提高了0％～40％。该方法能够准确地评价图像聚焦的程度，并具有较高的灵敏度和较强的抗噪性。

基于数字图像处理的自控显微镜聚焦算法研究

自动聚焦的评价函数是基于数字图像处理的自动聚焦算法的关键问题。从空域和频域详细分析了离焦图像的成像原理,利用带步长的拉普拉斯算子比较了一系列模糊图像的清晰度。改进的拉普拉斯算子结合爬山法能够实现自控显微镜的高效率精确聚焦,是一种简洁实用的聚焦策略。改进后的聚焦评价函数具有灵敏度高、单峰值、无偏离、计算量小和较高的信噪比等特点。实验表明,与传统的梯度算子聚焦算法相比较,改进的自动聚焦算法效率更高,聚焦位置更精确。

简析光学系统自动调焦的方法

自动调焦技术已经广泛应用于各种光学仪器中。常见的调焦方法,从基本原理上可分成基于物方测距的主动式和基于像检测法的被动式两大类。主动、被动式自动对焦方式各有千秋,主动式由系统主动发出光波,可以在低反差、弱光线下对焦,但当被摄体能吸收或反射光或波时对焦困难。被动式直接接收来自景物自身的反光,对具有一定亮度的被摄体能理想地自动对焦,自身不要发射系统,耗能少,有利于小型化。被动法中的以数字图像处理作为调焦检测函数的方法,理想的评价函数要求无偏性、单峰性、能反映离焦的极性、对噪声敏感度低等。为提高效率,往往还希望计算量尽可能地小。文章介绍了目前应用于光学系统的几种基于光电测试和图像处理的自动调焦方法。

一种用于数字成像的自动对焦系统

提出一种用于数字成像的自动对焦系统,它以CMOS为图像传感器,用DSP进行数据处理并控制驱动电路调整镜头的位置,达到准确自动对焦的目的。系统采用对焦深度法实现自动对焦,通过改变镜头的位置获得一系列模糊程度不等的图像,计算每幅图像的清晰度评价值构成对焦评价曲线;采用梯度函数作为评价标准来评价图像的清晰度;采用窗口选择技术控制对焦感兴趣范围,减少了数据处理量;对实验样机的测试表明,系统有较好的自动对焦性能,并解决了百叶窗问题,对透过玻璃窗户的目标仍然能正确对焦。

采用最大灰度梯度法实现经纬仪自动调焦控制

提出了一种基于最大灰度梯度的经纬仪自动对焦方法,以CMOS相机为图像传感器,用计算机进行数据处理并控制驱动电路调整相机镜头的位置来实现自动调焦。首先,选择包含主体成像目标的最小区域作为对焦选择区域,不仅有效地节省了系统处理图像的时间,而且极大地减小了复杂背景对精确调焦的干扰,提高了调焦准确率;其次,求出边缘上任意可能梯度方向的梯度,比较后得到每个边缘点的最大梯度;最后,采用最大灰度梯度作为系统的自动聚焦判距。实验结果表明,系统的调焦分辨率为0.01～0.02mm,能够满足经纬仪第一像面焦深的调焦要求。该调焦算法具有单峰性强、无偏性好、灵敏度高、稳定性好以及可实时性操作等特点。