Efficient randomized Hough transform for circle detection using novel probability sampling and feature points

This paper presents an efficient randomized Hough transform algorithm for circle detection. It optimizes the methods for determining sample points and finding candidate circles. Due to these two optimizations, sampling validity is improved and many false circles are prevented from being regarded as candidate circles. Experimental results demonstrate that the proposed algorithm, which features a strong robustness and high resolution, can dramatically speed up circle detection as compared to other algorithms. It can also be applied to detect ellipses.     

基于改进Hough变换的井盖目标检测与定位

市政井盖的实时告失对城市管理具有重大意义。针对图像的复杂背景,提出了改进的Hough变换算法。在经边缘提取的二值图上,利用轮廓跟踪找到所有的轮廓,接下来设计轮廓过滤器排除虚假目标,进而在轮廓链表上进行Hough变换从而确定目标可能出现的区域,最终获得准确的井盖区域定位。该方案有效地提高了传统Hough变换的处理速度,减少了无效采样和累积。实验结果表明,该算法在多种复杂背景、不同视角、不同拍摄时间和条件、目标被部分遮挡等情况下都有很好的定位效果。     

Human eye localization using the modified Hough transform

The precise localization of parts of a human face such as mouth, nose or eyes is important for their image understanding and recognition. The developed successful computer method of eyes and eyelids localization using the modified Hough transform is presented in this paper. The efficiency of this method was tested on two publicly available face images databases and one private face images database with the location correctness better than 96% for a single eye or eyelid and 92% for eye and eyelid couples.     

利用广义霍夫变换对相交目标进行轨迹预测

提出一种广义霍夫变换方法对相交目标进行轨迹预测,该方法利用概率分布原理,在参数空间中寻找点分布最集中的区域,以确定目标轨迹二次曲线方程的系数。为了提高搜索速度,提出采用投影法定位二次曲线方程的系数,从而使该方法满足实时性要求。该方法抗噪性强,克服了最小二乘轨迹预测法对噪声敏感的缺点。实验中采用最小二乘法和广义霍夫变换对相交目标进行轨迹预测,目标分离时正确匹配率分别为87.5%和95%。     

Fourier transform detection system for rotating-analyzer ellipsometers

An ellipsometry technique, based upon on-line Fourier analysis of the transmitted light intensity of a rotating-analyzer ellipsometer by means of a minicomputer, is presented and discussed. In addition to permitting great data processing flexibility, the method circumvents many difficulties inherent in present analog systems and enables much higher precision to be obtained.     

一种直线检测的尺蠖蠕行算法

从仿生学的角度提出了一种新的直线检测的尺蠖蠕行算法(cankerworm crawlalgorithm)。该算法首先根据梯度方向将边缘像素集合划分成为具有一定梯度范围的子集,然后采用蠕行策略在独立的边缘点的子集内进行直线提取。理论分析和实验结果证明:该方法大大减小了直线特征提取的复杂度,并且具有较好的直线检测效果。     

Estimation of red blood cell aggregate velocity during sedimentation using the Hough transform

A method for velocity estimation of sedimenting three-dimensional (3D) red blood cell (RBC) aggregates by means of an image processing technique is proposed. Successive images of RBC suspension near the wall of a container reveal rouleaux formation, sedimentation of 3D RBC aggregates and formation of the deposit of the cells. Plots of the position versus time for the 3D RBC aggregates were extracted by a processing of successive images of the suspension. The plots exhibit a quasi-linear structures in noisy background. With the use of the Hough transform the detection of the slope of the structures was performed and the velocity of the aggregates was estimated. To show the potential of the method spatio-temporal dependence of the aggregate velocity is presented for RBCs in plasma, RBCs in Dextran and for hardened cells at haematocrit 5%.     

Iris localization based on the Hough transform,a radial-gradient operator,and the gray-level intensity

The iris biometric recognizes a human based on his/her iris texture, which is a stable and unique feature for every individual. A typical iris biometric system performs better for the ideal data, which is acquired under controlled conditions. However, its performance degrades when localizing iris in non-ideal data containing the noisy issues, e.g., the non-uniform illumination, defocus, and non-circular iris boundaries. This study proposes a reliable algorithm to localize iris in such images robustly. First, a small region containing the coarse location of iris is localized. Next, the pupillary boundary is extracted within this small region using an iterative-scheme comprising an adaptive binarization and a pupil location verification test. Following that, the limbic boundary is localized by reusing the Hough accumulator. The iris location is also verified through a gray-level test. After that, the pupillary and limbic boundaries are regularized by applying an enhanced method comprising a Radial-gradient operator (RGO), an error-transform (ET), and the Fourier series. Experimental results, obtained on the CASIA-IrisV3, CASIA-IrisV4, MMU V1.0, and MMU(new) V2.0 iris databases, show superiority of the proposed technique over some of the contemporary techniques.     

一种新的不规则直线段识别方法

在立式风洞飞机尾旋运动姿态测量实验中,由于拍摄角度以及光照等原因,飞机表面直线段标识成像不是十分规则,直线段特征难于识别。对此,提出了一种新的不规则直线段识别方法。该方法利用一定尺寸的模板窗口沿直线段移动,根据模板中心的移动轨迹判断检测结果。模板的移动以检测窗口质心对中心的偏移量为动力,以检测窗口有效像素百分比、线段延伸方向和移动步数等参数为控制检测结果。该方法的检测过程类似于小球滚过宽度相当的凹槽,故又称为基于滚球原理的直线段检测方法。实验证明,该方法具有较好的稳定性,对直线段的变形来说具有一定的容错性,对检测参数的调整来说可控制检测对象的宽度和直线段不规则性的允许程度,无论是对仿真图像还是对实测图像中的直线段特征都具有较好的检测结果。     

Principal component analysis for emergent acoustic signal detection with supporting simulation results

A method is introduced that uses principal component analysis (PCA) to detect emergent acoustic signals. Emergent signal detection is frequently used in radar applications to detect signals of interest in background clutter and in cognitive radio to detect the primary user in a frequency band. The method presented differs from other standard techniques in that the detection of the signal of interest is accomplished by detecting a change in the covariance between two channels of data instead of detecting the change in statistics of a single channel of data. For this paper, PCA is able to detect emergent acoustic signals by detecting when there is a change in the eigenvalue subspace of the covariance matrix caused by the addition of the signal of interest. The algorithm's performance is compared to an energy detector and the Neyman-Pearson theorem. Acoustic simulations were used to verify the performance of the algorithm. Simulations were also used to examine the effectiveness of the algorithm under various signal-to-interferer and signal-to-noise ratios, and using various test signals.     

Voigt line infrared atmospheric transmittance calculations by Fourier transform

The absorption coefficient space of an i.r. atmospheric path contains the linear superposition of many Voigt spectral lines. This paper discusses the practical application of Karp's method to the simulation of satellite transmittance and radiance observations by using fast Fourier transforms on the recursively generated Voigt transforms. Although the procedure is physically straightforward, it is nonetheless computationally demanding and suited primarily to narrow isolated Q-branch regions. Performing the calculation on a 2.4 cm^-1 wide 15 μ CO₂Q-branch region demonstrates that 4% of the total absorption takes place above 0.1 mb. This absorption is in the cold mesopause and results in a 1–2% radiation deficit with its inclusion in a satellite radiation calculation.     

Nonlinear joint fractional Fourier transform correlation for target detection in hyperspectral image

In this paper, we present a spectral joint fractional Fourier transform correlation (SJFRTC) for detecting and identifying very small target with only a few pixels using reflectance spectral information in the hyperspectral imagery. In this technique, fractional correlation (FC) between input spectral signature and known reference spectral signature is performed digitally or optically. Binary differential technique is utilized to enhance the performance of the SJFRTC, resulting in delta-function-like correlation peaks without dc interference. Distinctive and distinguishable correlation performance is obtained using peak-to-clutter ratio (PCR) instead of absolute correlation peak value, which makes the proposed technique independent from the intensity variation of the spectral signature. Simulation results using real-life hyperspectral images show that the binary SJFRTC can detect both single or/and multiple targets successfully with excellent detection capability, as compared to the other traditional hyperspectral detection algorithms.     

Improved approach for target detection and recognition on optoelectronic hybrid joint transform correlator

A conventional joint transform correlator (JTC) often generates large correlation sidelobes as well as a large correlation peak width, strong zero-order peak, and low diffraction efficiency in target detection and recognition, which make the detection ability of JTC lower. To conquer these difficulties, firstly, a joint power spectrum (JPS) subtraction technique was proposed in Fourier plane, where power spectrum of reference image and power spectrum of object image are subtracted from the JPS before inverse Fourier-transform operation, it is evident that the improved JPS removes the zero-order term. Secondly, a fringe-adjusted filter (FAF) was presented to restrain sidelobes and noises. The revised JPS is multiplied by a FAF before the inverse Fourier-transform operation to obtain the cross-correlation peak. Computer simulations showed the improved method can markedly eliminate zero-order diffraction and effectively control the sidelobes and noises compared to traditional JTC, and then enhance the detection ability for JTC. Experimental results presented the sharp correlation peak and also demonstrated this approach effectiveness.     

基于高帽变换算法的液位检测技术的研究

将数学形态学中的高帽变换算法应用于液位高度的检测之中。利用形态学高帽变换,并选用大结构元素,对具有复杂背景的比色皿中的液位图像和分层液位图像进行处理,实现了液位高度的快速准确检测。实验结果表明,该方法适用于医学生化分析仪比色皿中样品液位高度的检测,其原理也可以用于其他工业装置中的液位高度检测。     

一种基于逆投影变换的智能车道路识别方法

针对智能车辆实验环境,提出了一种基于单目视觉的智能车辆道路识别方法。该方法对智能车辆在行驶过程中采集的图像进行逆投影变换,消除透视投影对道路识别的影响,并且可以根据视觉导航的需要选择部分兴趣区域进行投影变换。再对道路俯视图进行中值滤波、边缘检测,有效地提取出了道路的边缘图像。该方法还提出了简易的道路模型,提高了视觉导航的实时性。     

基于平稳小波变换的有噪弱目标检测方法的研究

利用平稳小波变换的多尺度边缘检测算法分别对模糊图像、低对比度图像和加入噪声的图像进行了边缘检测,验证了多尺度二次B样条小波的检测效果,也比较了三种小波局部模极大值方法在抗噪性、计算量及检测效果等方面的性能,并且针对对比度低,受噪声污染严重的目标图像,提出一种能够根据不同背景计算出自适应阈值的新方法,使其在抗噪的同时又能较好地提取出微弱目标边缘。实验证明,利用多尺度二次B样条小波边缘检测算法能有效地排除噪声干扰,准确地提取出微弱边缘,可以实现3%对比度下的有噪图像的目标探测问题。     

第四讲探潜先锋--拖曳线列阵声纳

文章介绍了在反潜战中发挥重要作用的拖曳线列阵声纳的工作原理、结构特点、系统组成,同时回顾了拖曳线列阵声纳从第一次世界大战时Hayes H C博士的概念到2000年John R.Potter等人的细线阵所经历的长达80年的发展过程,最后预计,应用光纤、新声源,采用多线阵结构能进行三维定位的主被动模块化拖曳线列阵声纳是未来的发展方向.     

一种基于边缘的曲波变换图像融合方法

提出了一种新的图像融合方法。采用Canny边缘检测方法,并结合曲波变换算法,确定图像边缘位置。针对曲波分解的不同频率域,对高频信息依据其是否为边缘点采用不同的融合策略,对低频信息利用平均法进行融合,最后进行重构得到融合结果。对该方法得到的实验结果进行主客观评价和对比表明,提出的算法在抑制噪声的同时,能有效地突出边缘细节,具有更好的视觉效果。     

Robust pedestrian detection in thermal infrared imagery using the wavelet transform

A novel and robust pedestrian detection method in thermal infrared images based on the double-density dual-tree complex wavelet transform (DD-DT CWT) and wavelet entropy is presented in this paper. The regions of interest (ROIs) are located first making use of high brightness property of the pedestrian pixels caused by the self-emission of the pedestrians related to the Planck’s law. The candidate ROIs are then decomposed by DD-DT CWT and the wavelet entropy features are extracted from the high frequency subbands. The true pedestrian regions are finally classified and recognized using the support vector machine (SVM) classifier. Comparisons between our approach and traditional approaches are presented and experimental results using several thermal infrared image databases show the proposed scheme to be very promising.