基于ARM处理器的运动目标检测与跟踪系统

运动目标的检测及跟踪技术广泛应用于军事与民用领域。传统基于PC的目标跟踪系统不能满足对体积、功耗及便携性的需求,基于ARM处理器S3C2440A和嵌入式Linux操作系统构建了一个比较完整、实用的目标跟踪系统。该系统利用摄像头采集运动目标图像,处理器进行数字图像处理,LCD显示跟踪目标。阐述了实现原理及图像获取、目标检测、图像分割和目标跟踪算法程序流程。通过实际测试,该系统能满足对低速运动目标的检测、识别和跟踪,且具有较好的实时性和稳定性。     

基于二维重组和动态窗格的水质检测紫外-可见光谱去噪算法

立足于成功研制的紫外-可见光谱水质检测多参数测量系统,针对紫外-可见光谱水质多参数原位实时检测在精度、灵敏度、稳定性等方面的实际需要,开展了基于二维重组和动态窗格的水质检测紫外-可见光谱去噪算法的研究,以此提高紫外-可见光谱水质检测的测量精度。光谱法水质检测系统通常使用工业级低成本光谱仪,其输出光谱包含明显的非平稳噪声。传统去噪法难以在滤除噪声的同时保留谱线细节。而且,原位实时水质检测条件下,被测水样可能快速变化,传统去噪法中常用的多次采样求均值法将产生额外的测量误差。引入的去噪算法通过对水样光谱进行等间隙连续采样,将光谱数据张成由光谱轴和时间轴构成的二维矩阵,经过二维小波变换后,设置一个可变宽度的窗格在系数矩阵中水平滑动,使用窗格内的小波系数计算得到动态去噪阈值,并随窗格滑动构建去噪阈值向量,由此进行光谱去噪。其中,窗格宽度由相邻区域的噪声方差变化率决定,变化率较高的区域缩小窗格宽度,反之则扩大宽度。实验结果表明,这种去噪算法不仅能有效去除光谱中的非平稳噪声,而且能保留光谱的细节信息,有助于提高仪器的测量精度。与此同时,由于该算法并未使用时域平均,样本的快速变化对去噪性能的影响较小,适合在线或原位水质检测的水样本环境。     

可见/近红外光谱的油茶籽油三元体系掺假检测模型优化

采用可见/近红外光谱技术结合化学计量学方法对油茶籽油三元体系掺假进行定量检测研究。将菜籽油和花生油按不同比例掺入纯油茶籽油中,获得掺假样本。采集纯油茶籽油及掺假样本在350~1 800 nm范围内的可见/近红外光谱数据,随机分为校正集和预测集,并从不同建模波段、预处理方法及建模方法角度对掺假预测模型进行优化。研究结果表明,菜籽油、花生油和总掺伪量的最优建模波段及预处理方法分别为750~1 770,900~1 770 ,870~1 770 nm和多元散射校正(MSC)、标准归一化处理(SNV)和二阶微分,而最优的建模方法均为最小二乘支持向量机(LSSVM)。对于最优掺假模型,菜籽油、花生油和总掺伪量的预测集相关系数(R_p)和预测均方根误差(RMSEP)分别为0.963,0.982,0.993和2.1%,1.5%,1.8%。由此可见,可见/近红外光谱技术结合化学计量学方法可以用于油茶籽油的三元体系掺假定量检测。     

基于荧光分析的氨基甲酸酯类农药残留检测系统

通过对氨基甲酸酯类农药在紫外光照射下能够产生荧光的机理研究,设计了一种用于检测氨基甲酸酯类农药残留的荧光系统。该系统采用单光源、双光路结构,能够对测量信号和参考信号同时进行处理。采用所设计的筒式光纤探头激发并探测荧光,设计了相应的信号处理电路,实现了计算机管理。利用该系统和稳态光谱仪对西维因进行了对比实验。结果表明:在激发波长为319nm、荧光波长为654nm时,最小检测浓度为5×10-7μg/L。当西维因浓度范围在0.0～120.0μg/L之间时,系统具有较好的线性关系,线性相关系数r=0.9996(信噪比S/N=5)。该系统达到了荧光检测的指标。     

一种基于图像融合的运动目标快速检测算法

提出了一种新的运动目标检测方法,这种方法可以有效的提取目标轮廓。应用一种图像差分技术得到运动目标的初始轮廓线。使用了动态轮廓线使其收敛到目标轮廓。提出了一种新的目标轮廓特征级融合方法,求解两类模式图像的收敛动态轮廓线控制点向量差的范数平方极小化。这种方法不需要图像配准降低了融合的计算复杂度,有效提高了可见光图像中目标轮廓提取的精度。对比检测实验证实了算法的有效性。设计了一种基于Newmark方法的动态轮廓线快速迭代算法,将该方法和方法作了比较,对比实验表明这种方法的时间复杂度降低了22%。     

新型长周期光纤光栅的横向负载特性及其偏振相关性研究

发现高频CO2激光脉冲写入的长周期光纤光栅谐振波长的横向负载特性具有较强的负载方向相关性,而损耗峰幅值的横向负载特性的方向相关性较弱.不同圆周方向的横向负载对谐振波长偏振相关性的影响差异较大,但对损耗峰幅值偏振相关性的影响差异较小.利用横向负载引起双折射进而导致光栅的光学主轴旋转的相关理论,合理解释了该长周期光纤光栅独特的横向负载特性及其偏振相关性.     

Cooling overall spin temperature: protein NMR experiments optimized for longitudinal relaxation effects

In experiments performed on protonated proteins at high fields, 80% of the NMR spectrometer time is spent waiting for the ¹H atoms to recover their polarization after recording the free induction decay. Selective excitation of a fraction of the protons in a large molecule has previously been shown to lead to faster longitudinal relaxation for the selected protons [K. Pervushin, B. Vögeli, A. Eletsky, Longitudinal ¹H relaxation optimization in TROSY NMR spectroscopy, J. Am. Chem. Soc. 124 (2002) 12898–12902; P. Schanda, B. Brutscher, Very fast two-dimensional NMR spectroscopy for real-time investigation of dynamic events in proteins on the time scale of seconds, J. Am. Chem. Soc. 127 (2005) 8014–8015; H.S. Attreya, T. Szyperski, G-matrix Fourier transform NMR spectroscopy for complete protein resonance assignment, Proc. Natl. Acad. Sci. USA 101 (2004) 9642–9647]. The pool of non-selected protons acts as a “thermal bath” and spin-diffusion processes (“flip-flop” transitions) channel the excess energy from the excited pool to the non-selected protons in regions of the molecule where other relaxation processes can dissipate the excess energy. We present here a sensitivity enhanced HSQC sequence (COST-HSQC), based on one selective E-BURP pulse, which can be used on protonated ¹⁵N enriched proteins (with or without ¹³C isotopic enrichment). This experiment is compared to a gradient sensitivity enhanced HSQC with a water flip-back pulse (the water flip-back pulse quenches the spin diffusion between ¹H^N and ¹H^α spins). This experiment is shown to have significant advantages in some circumstances. Some observed limitations, namely sample overheating with short recovery delays and complex longitudinal relaxation behaviour are discussed and analysed.     

Auxiliary probe design adaptable to existing probes for remote detection NMR, MRI, and time-of-flight tracing

A versatile, detection-only probe design is presented that can be adapted to any existing NMR or MRI probe with the purpose of making the remote detection concept generally applicable. Remote detection suggests freeing the NMR experiment from the confinement of using the same radio frequency (RF) coil and magnetic field for both information encoding and signal detection. Information is stored during the encoding step onto a fluid sensor medium whose magnetization is later measured in a different location. The choice of an RF probe and magnetic field for encoding can be made based solely on the size and characteristics of the sample and the desired information quality without considering detection sensitivity, as this aspect is dealt with by a separate detector. While early experiments required building probes that included two resonant circuits, one for encoding and one for detection, a modular approach with a detection-only probe as presented here can be used along with any existing NMR probe of choice for encoding. The design of two different detection-only probes is presented, one with a saddle coil for milliliter-sized detection volumes, and the other one with a microsolenoid coil for sub-microliter fluid quantities. As example applications, we present time-of-flight (TOF) tracing of hyperpolarized (129)Xe spins in a gas mixture through coiled tubing using the microsolenoid coil detector and TOF flow imaging through a nested glass container where the gas flow changes its direction twice between inlet and outlet using the saddle coil detector.     

自然地面背景下红外目标检测算法

为了快速准确地检测出以地面物体为背景的红外序列图像中的目标,结合小波变换的特点及其应用于图像边缘检测的优点,提出了一种基于小波技术的图像预处理算法。该方法利用图像边缘在目标识别中的重要作用,讨论了基于小波变换的图像边缘检测方法,并结合地面背景红外图像自身的特点,大大地提高了单帧的检测概率。     

Characteristic properties of the conical Mueller matrix

We present results of mathematical relations existing between the Mueller matrix obtained for an in-plane of incidence scattering geometry (plane Mueller matrix, PMM) and the Mueller matrix obtained for an out-the-plane of incidence scattering geometry (conical Mueller matrix, CMM), for light scattered from a rough surface. We obtain a similarity relation between the CMM and the PMM for one- (1-D) and for two-dimensional (2-D) surfaces. This similarity relation implies that the PMM and the CMM have the same determinant, trace and eigenvalues for 1-D and 2-D surfaces, respectively. We can say that measurements made in the conical geometry are “Similarity Equivalent” to those in the in-plane geometry for both kind of surfaces, respectively.