基于光电成像技术的运动员垂直弹跳高度测试

针对运动员弹跳过程持续时间短,弹跳位置相对不固定,弹跳高度测试操作复杂的问题,提出一种基于线阵光电成像技术的运动员垂直弹跳高度测试方法;首先构建大视场垂直弹跳高度测试系统,线阵CCD相机进行实时获取,得到目标弹跳轨迹图像;然后对目标弹跳轨迹图像进行图像分析和处理,高精度提取弹跳特征点,从而获得运动员垂直弹跳的运动时间;最后依据运动学公式,实现运动员垂直弹跳高度的准确测试;进行多组实验并分析实验数据,结果表明在1500mm的弹跳测试范围内,实验相对误差范围在3%以内,证明了该方法的可行性。     

四谱段TDICCD图像传感器的设计与制作

设计并研制了一种四谱段时间延迟积分电荷耦合器件(TDICCD)图像传感器,器件将四个TDICCD集成在同一芯片上,通过在光窗对应位置上镀不同的窄带滤光膜实现多谱段分光。该TDICCD图像传感器的像元尺寸为28μm×28μm,水平寄存器的有效像元数为3 072元,行频为10 kHz,电荷转移效率高达0.999 99,饱和输出电压为2 650 mV,抗弥散能力大于等于100倍,动态范围为7 143∶1。     

Bond line thickness and die tilt inspection in die bonding process

This study focuses upon building an automated inspection system for the in-line measurement of bond-line thickness (BLT) and die tilt in die attachments in the semiconductor packaging process. A prototype of a visual system utilizing the line scan stereo vision technique via two linear CCD cameras has been developed for the die bonding quality inspection. A novel algorithm is proposed for the determination of the 3D coordinates of certain points on an object. The BLT and die tilt of a die attached chip of substrate height 800 μm and cross section 15 × 15 mm² were measured to be approximately 76.8 μm and 0.00094, respectively. The measurement can be completed within one second. Thus the in-line inspection of die bonding quality can be conducted efficiently using the proposed technique.     

基于角度不变的线阵推扫式CCD相机几何畸变在轨检校方法

对航天遥感相机进行在轨检校,是提高卫星产品质量,扩大产品应用效果的重要技术内容.文中研究了一种基于角度不变的线阵推扫式CCD相机几何畸变在轨检校方法.该方法利用相机外方元素对于相机视向量夹角角度影响比较小的原理,根据地面控制点和一级产品图像,求解相机视向量夹角,从中提取相机光学部件的畸变模型参数,从而实现相机内外方元素解耦.相机畸变模型采用一维3阶多项式,对焦距和主点等引起的低阶误差能够很好地吸收.该方法用在HJ-1A/B卫星的宽幅盖CCD相机几何畸变校正上,检校误差残留在2—6个像元,和参考数据精度相似,表明取得了很好的校正效果.     

Robust metric calibration of non-linear camera lens distortion

Camera lens distortion is crucial to obtain the best performance cameral model. Up to now, different techniques exist, which try to minimize the calibration error using different lens distortion models or computing them in different ways. Some compute lens distortion camera parameters in the camera calibration process together with the intrinsic and extrinsic ones. Others isolate the lens distortion calibration without using any template and basing the calibration on the deformation in the image of some features of the objects in the scene, like straight lines or circles. These lens distortion techniques which do not use any calibration template can be unstable if a complete camera lens distortion model is computed. They are named non-metric calibration or self-calibration methods.Traditionally a camera has been always best calibrated if metric calibration is done instead of self-calibration. This paper proposes a metric calibration technique which computes the camera lens distortion isolated from the camera calibration process under stable conditions, independently of the computed lens distortion model or the number of parameters. To make it easier to resolve, this metric technique uses the same calibration template that will be used afterwards for the calibration process. Therefore, the best performance of the camera lens distortion calibration process is achieved, which is transferred directly to the camera calibration process.     

Revisiting Zhang's 1D calibration algorithm

In recent years, the camera calibration using 1D patterns has been studied and improved by researchers all over the world. However, the progress in that area has been mainly in the sense of reducing the restrictions to the 1D pattern movement. On the other hand, the method's accuracy still demands improvements. In the present paper, the original technique proposed by Zhang is revisited and we demonstrate that the method's accuracy can be significantly improved, simply by analyzing and reformulating the problem. The numerical conditioning can be improved if a simple data normalization is performed. Furthermore, a non-linear solution based on the Partitioned Levenberg-Marquardt algorithm is proposed. That solution takes advantage of the problem's particular structure to reduce the computational complexity of the original method and to improve the accuracy. Tests using both synthetic and real images demonstrate that the calibration method using 1D patterns can be applied in practice, with accuracy comparable to other already traditional methods.     

Analysis and evaluation of a general camera model

A versatile General Camera Model, GCM, has been developed, and is described in detail. The model is general in the sense that it can capture both fisheye and conventional as well as catadioptric cameras in a unified framework. The camera model includes efficient handling of non-central cameras as well as compensations for decentring distortion. A novel way of analysing radial distortion functions of camera models leads to a straightforward improvement of conventional models with respect to generality, accuracy and simplicity. Different camera models are experimentally compared for two cameras with conventional and fisheye lenses, and the results show that the overall performance is favourable for the GCM.     

基于OpenCV的改进两步法摄像机标定

采用改进两步法实现了摄像机的标定,并给出基于OpenCV算法,充分发挥了OpenCV的函数库功能。对两步标定法的改进是在原两步法得到摄像机参数值的基础上,用非线性优化算法对所有参数进一步优化,得到最终参数值,既提高了摄像机标定精度和计算效率,又无需对摄像机像面中心预标定,简化了标定过程。     

基于角点的监控摄像头干扰检测

提出一种新的实时检测摄像头干扰的方法,建立一种基于最小核值相似区SUSAN(Smallest Univalve Segment AssimilatingNucleus)角点的图像特征函数,由于干扰发生时相对的几帧图像与正常图像相比会发生显著变化,因此通过比较图像的特征函数值来检测干扰的发生。利用一种逻辑判断方法做到对突变和渐变干扰的全面检测,并且避免对无害行为的误检,使之更具鲁棒性。对比已有的方法,分别对不同场景及不同类型的摄像头遮挡和转动干扰进行了多组测试,实验结果显示,该方法明显优于其它算法,能够很好地检测出对摄像头的遮挡及转动干扰,并且很好地避免了对无害行为的误检。     

基于人工神经网络的CCD数码相机颜色特征化

阐述了基于BP神经网络的数码相机特征化方法。采用不同的神经网络结构,建立了数码相机记录的RGB信息和原影像C IEXYZ色度信息之间的非线性对应关系。对NIKON D200数码相机进行了研究,通过实验得到了合理的神经网络结构为3—10—10—3。测试不同的训练样本和测试样本,达到的C IELAB平均色差和最大色差分别为1.9~2.2和6.7~7.4个色差单位。讨论了实验设备的重复性,同时,分析了样本数量对实验结果的影响。实验结果表明:对数码相机的特征化,可采用BP神经网络技术实现较高的精度。