用于数码相机的瞳孔控制自动对焦技术

对焦窗口的选择是数码相机进行自动对焦的关键问题之一。现有的对焦窗口的选择方法过于简单,由于成像目标的复杂性,有必要使对焦窗口的选择本身实现自动化和智能化[1]。提出了一种利用数字图像处理来进行瞳孔控制自动对焦的方法。对现有照相机结构稍加改进后,可以利用数码相机中现有的CCD/CMOS图像传感器获取拍摄者眼睛的图像,再通过对拍摄者眼睛的图像进行处理来判断其瞳孔在眼睛中的位置。根据这一位置信息,可以推断拍摄者的注意力所集中的区域,从而对焦窗口的自动选择。     

基于对焦深度法的光学显微镜系统设计

针对传统显微镜采用手工对焦方式存在自动化程度低、对焦过程较慢且对操作者经验要求高的问题,提出一套基于对焦深度法的光学显微镜系统。结合基于图像处理自动对焦的显微镜通用结构,设计了一套由ARM开发板、触控液晶显示屏、Arduino UNO开发板、红外对管、工业数码显微镜及步进电机等组成的光学显微镜系统。结合触控液晶显示屏的特点,设计出结合不同大小的感兴趣区域对焦窗口选择方法,并在采用常见梯度函数作为图像清晰度评价函数及爬山搜索算法的基础上,提出容错改进方法。实验分别对不同的图像清晰度评价函数及对焦窗口大小进行了实时性、灵敏度及容错性能测试。结果表明,该系统具有较高的可靠性。     

基于简化对焦模型的自动对焦窗口调整方法

提出一种基于简化对焦模型的自动对焦窗口调整方法用于数码相机自动对焦过程.根据初始对焦窗口和初始像距计算初始对焦窗口边界的视场角,镜头位置改变后,再根据此视场角和新的像距计算新的对焦窗口边界,进而调整对焦窗口,实现景物跟随.实验结果表明,该方法能够在物距未知的情况下近似地计算出目标的像高,与固定对焦窗口相比,能够避免背景信息的干扰,使评价函数具有单峰性.且该方法计算过程与图像内容无关,不受图像模糊程度的影响.     

数字成象系统自动对焦区域设计

本文从摄影艺术的角度,提出一种对焦区域选择策略.经实验证明,这种区域选择策略可以提高多景深场景的自动对焦的有效性,并可作为一种自动对焦模式预置于数字成象系统中,从而把传统摄影技术中的各种经验知识结合到对焦区域设计的策略中,使以对焦为关键技术的数字相机、数字摄象机从原理上被人们所接受.     

基于彩色图象 RGB分析的自动对焦技术

参照人眼的特点,作者将传统的双焦评价函数分别作用于目标图象的R、G、B分量得到三个数值,然后由这三个值计算出一个新的评价值.对一般对焦目标,这种新方法能增强传统对焦评价函数结果.本文中作者对这一方法进行了详尽的讨论.     

自动对焦系统中图像非均匀采样的实验研究

将非均匀采样运用在自动对焦的窗口选择中,并进行了实验研究.这种方式可以保持中央的高分辨率,并保持较大的视场范围,克服了中央选窗时由于成像主体偏离中央引起的误对焦.同时,大大减少计算对焦评价函数所需的数据,从而加快对焦速度,促进对焦系统的实时化.     

数字对焦光场成像清晰度评价方法研究

结合光场成像数字对焦空间域算法和频率域算法的区别,分别提出了适用的图像清晰度评价方式,并进行了仿真实验分析.空间域评价方法根据评价区域缩小图像重构数据量,频率域评价方法则将评价函数嵌入到图像重构过程中,改进后的方法相对传统方法提高了速度.     

数字对焦光场成像清晰度评价方法研究

结合光场成像数字对焦空间域算法和频率域算法的区别,分别提出了适用的图像清晰度评价方式,并进行了仿真实验分析.空间域评价方法根据评价区域缩小图像重构数据量,频率域评价方法则将评价函数嵌入到图像重构过程中,改进后的方法相对传统方法提高了速度.     

基于表面图像锐度的LIBS自动对焦方法

利用自行设计的集成微区成像激光诱导击穿光谱系统,分析了孔径光阑设定、目标区域大小以及样品表面反射率对表面图像位置敏感特性的影响.结果表明,表面图像锐度在大孔径设定下对位置更为敏感,适用于自动对焦过程;反射率对表面图像锐度的位置敏感特性影响较小,且部分表面图像的锐度也可用于辅助激光诱导击穿光谱对焦;不同样品不同目标区域大小,图像锐度最大值对应表面位置具有很好的重复性.在此基础上,建立了基于表面图像锐度的自动对焦方法.     

基于视频图像处理的快速对焦方法研究

对焦速度与精度是自动对焦系统中最重要的两个参数,它们决定系统能否迅速地定位到焦点处,以获取清晰的图像。通过对比连续帧图像局部区域清晰度评价函数值来判断对焦趋势,同时控制对焦驱动电机的转动方向,最后进行反向搜索并与最大判据值比较以寻找到最佳成像位置,成功对焦所需最长时间小于2s。经过大量实验证明该方法具有较好的实时性和精确性。     

基于图谱理论的纹理图像分析

图谱理论作为目前模式识别研究的热门方法之一,广泛应用于聚类与分割,但对其进行图像分析,尤其是复杂的纹理图像分析未见报道。将图谱理论引入到图像分析领域,并结合窗口纹理分析方法构造新的纹理分析算法。首先对图像灰度级进行窗口划分得到不同灰度级下的子图像,然后以各子图像作为图的顶点,子图像间的相似度作为图的边,将原图像解析为一幅带权无向图。利用图谱理论的相关思想对该无向图进行分析,可以从中获得纹理粗糙度等特征,从而完成对原始图像的分析。通过对Brodatz图像库的检索实验证明,该方法优于传统纹理分析算法。     

Towards dynamic control of magnetic fields to focus magnetic carriers to targets deep inside the body

Magnetic drug delivery has the potential to target therapy to specific regions in the body, improving efficacy and reducing side effects for treatment of cancer, stroke, infection, and other diseases. Using stationary external magnets, which attract the magnetic drug carriers, this treatment is limited to shallow targets (<5 cm below skin depth using the strongest possible, still safe, practical magnetic fields). We consider dynamic magnetic actuation and present initial results that show it is possible to vary magnets one against the other to focus carriers between them on average. The many remaining tasks for deep targeting in-vivo are then briefly noted.     

Three-dimensional focus shaping with cylindrical vector beams

A three-dimensional focus shaping technique using the combination of cylindrical polarization with binary diffractive optical element is proposed. The energy density pattern at the vicinity of the focus can be tailored in three dimensions by appropriately adjusting the parameters of the cylindrical vector beam illumination, numerical aperture of the objective lens and the design of the binary diffractive optical element. Focus with extended depth of focus that has both transversal and longitudinal flattop profile is obtained. Optical bubble that has a total dark volume surrounded by high field distributions is also shown. Potential applications of this focus shaping technique are discussed.     

An algorithm for microscopic specimen delineation and focus candidate selection

In this paper, we compare four field-of-view (FOV) metrics that, when applied to a low-resolution image of a microscope slide, are capable of both accurately delineating the specimen and selecting a subset of focus candidate FOVs required for construction of high-resolution focus map. The metrics evaluated are: threshold index (TI) that measures image intensity; normalised auto-correlation index (NACI) that measures spatial image similarity; auto-phase correlation index (APCI) that measures image phase diversity; and entropy index (EI) that measures the predictability of image intensities. Experiments are undertaken on a data set of forty slides including PAP stained Thin-prep cervical cytology and breast fine-needle aspiration slides and haematoxylin and eosin (HE) stained histology slides. These slides were scanned on an automated bright-field microscope and chosen to be indicative of a variety pathology specimens, containing artefacts such as excess coverslip glue and ink markers. Results are presented on the performance of each metric for correct ranking/segmentation of foreground (specimen) from background, and subsequently selecting focus candidate FOVs characteristic of the specimen's focal plane(s). The experimental results demonstrate that while NACI, APCI and EI are all effective at specimen delineation, only APCI is capable of effectively selecting superior focus candidates and ignoring artefacts.     

视频自动聚焦的实现研究

摘要:     提出了用于会议电视摄像机的自动聚焦方法.该方法由聚焦调节和聚焦监测两个过程组成.聚焦调节是寻找聚焦函数最大峰值的过程,在该过程中通过利用超焦距概念和动态自适应变步长搜索算法加快搜索速度,并保证了良好的视觉效果|同时,提出退回检查最大值点变化方法,防止搜索过程中因受到场景变化干扰而导致的聚焦失败.聚焦监测过程是在会议电视通话中,通过监测场景变化使聚焦调节工作适时启动的过程,提出有条件地重新调节聚焦,以始终保障良好的摄像聚焦效果,同时避免频繁调焦.实验结果表明,提出的摄像机自动聚焦方法性能优秀并有良好的顽健性.该方法已经用于华为ViewPoint 8020plus视频会议终端的实际产品.     

基于视觉注意机制的感兴趣区检测

提出了一种基于视觉注意机制的感兴趣区检测方法：使用分水岭方法分割图像区域;根据生物的视觉注意机制特性,选用中央周边差的采样方式提取图像特征,将不同维的图像特征融合为显著图;显著点经过竞争得到的注意焦点作为分水岭分割的种子点,然后融合显著图和分水岭分割区得到感兴趣区;遵循返回抑制和邻近优先的准则选择并转移注意焦点,从而计算区域的重要性或兴趣度.实验结果表明该方法符合生物的视觉注意机制,在自动检测感兴趣区时可以有效减少过分割,也能较好的处理大对象.     

Image restoration of skin scattering and optical blurring for finger vein recognition

Finger vein recognition has been adopted due to its high recognition rate and the invisibility of vein in visible light. However, because a finger vein pattern is not distinctive due to light scattering in the skin layer, the localization of a finger vein pattern region using an image processing algorithm is a difficult procedure. Also, optical blurring increases these difficulties. We propose a new finger vein image restoration method to deal with skin scattering and optical blurring. Our research is novel in three ways compared to previous studies. Firstly, the amount of optical blurring of a finger vein image is measured based on the average gradient of the orthogonal profile of a finger edge. Secondly, the accurate point spread function (PSF) of optical blurring is adaptively determined based on the orthogonal profile of a finger edge. Thirdly, using a constrained least square (CLS) filter and optimized parameters in terms of the lowest error of finger vein recognition, the restoration of a skin scattered and optically blurred finger vein pattern was performed. Experimental results show that the equal error rate (EER) of finger vein recognition with restoration was reduced by as much as 3.14% (5.05-1.91%) compared to the EER without restoration.