Cooperative matching paradigm for the analysis of stereo image sequences

A general framework for the analysis of sequences of stereo images is presented in this article. The proposed paradigm integrates spatial and temporal information to achieve robustness in establishing stereo correspondence from images that possess a limited number of salient features. Specifically, the recovery of dynamic stereo information, and thus, the reconstruction of a three-dimensional object structure, is accomplished using a feature-based approach. The multiset feature correspondence problem is cast into a four-dimensional problem which is subsequently solved using a greedy-type local search algorithm. No assumption is made about the type of motion. The proposed algorithm may be applied to process image sequences containing both rigid and nonrigid shapes. The efficacy of the proposed approach is tested using both synthetic data and real images of a live frog's ventricle acquired by a stereo light microscope. We also consider the incorporation of domain-specific knowledge to enhance the performance of the cooperative matching scheme. © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 192–200, 1998     

Estimating building dimensions from synthetic aperture radar image sequences

The problem of automatically extracting building dimensions from synthetic aperture radar (SAR) image sequences of urban scenes is considered. An algorithm based on the delineation of shadows using active contours constrained by a simple wire-frame building model has been developed and demonstrated using SAR imagery of a village on Salisbury plain. The core of the algorithm is a novel technique for target delineation involving multiple active contours evolving simultaneously. In particular, a technique referred to as multiple hypothesis delineation, in which contours can be in several states simultaneously, is developed and shown to lead to considerable improvement in convergence time and delineation accuracy when used to delineate multiple targets in close proximity. The technique is applied to the automatic estimation of building dimensions by delineation of shadows in a sequence of SAR images of an urban scene. The estimation of building dimensions is automatic; user interaction is limited identifying a building of interest and a region of background clutter close to the building. Results are presented for six different buildings, in each case two SAR images were used in the estimation process separated in illumination angle by either 28deg or 90deg. The estimates of building dimensions are compared with the actual building dimensions obtained from architectural drawings. The algorithm was found to perform robustly and provide reasonably accurate estimates of the building dimensions, typically within ~10% of the true values.     

Estimating the axle weight of vehicle in motion based on nonlinear curve-fitting

Dynamic tire forces are the main factor that influences the axle weight measurement accuracy. A nonlinear curve-fitting method is proposed to reduce the influence of the dynamic tire forces. After a brief introduction on the distinction between high-speed and weigh-in-motion low-speed weigh-in-motion and an analysis on the characteristic of the axle weight signal, the algorithm of the nonlinear curve-fitting and its implementation is presented in detail. Finally, the numerical simulation and field experiments are conducted to evaluate the performance of the proposed method. The results of simulation and field experiments prove the effectiveness of the proposed method. The maximum weighing errors of the front axle, the rear axle and the gross weights are 4.01%, 5.24% and 3.92%, respectively, at the speed of 15 km/h or lower     

Multiresolution image acquisition and surface reconstruction using active stereo

This paper is concerned with the problem of surface reconstruction from stereo images for large scenes having large depth ranges. The passive stereo paradigm is inadequate for this problem because of the need to aim cameras in different directions and to fixate at different objects. We present an active stereo approach in which the scene is systematically scanned and image acquisition and surface reconstruction are integrated using a four-step process. First, a new fixation point is selected from among the nonfixated, low resolution scene parts of current fixation. Second, a reconfiguration of cameras is initiated for refixation. As reconfiguration progresses, the images of the new fixation point gradually deblur and the accuracy of the stereo estimate of the point improves. In the third step, the improved stereo estimate is used to achieve accurate focus and vergence settings of the cameras for fixation. Finally, focus-based depth estimates are obtained at a grid near the fixation point whose density is determined by the local surface slope. These estimates are fused with those obtained from stereo using maximum likelihood (weighted averaging) and are interpolated to the non-grid points. This research was supported in part by the National Science Foundation under grantiri-89-11942, Army Research Office under grantdaal 03-87-K-0006, and State of Illinois Department of Commerce and Community Affairs under grant 90-103.     

Hausdorff距离下的景像特征快速匹配

针对灰度相关法鲁棒性差的缺点,提出一种以图像特征进行匹配的新方法。采用具有良好稳定性和旋转不变性的图像奇异值分解作为匹配特征,并根据奇异值的数值特点,采用规范化奇异值的Hausdorff距离作为特征匹配的相似性度量;通过变模板分级匹配的策略,在保证匹配精度的前提下,使匹配时间减少到约10%。在加入方差σ=35的高斯噪声,灰度变化25%的情况下对旋转变化的景像目标进行匹配实验,结果证实了本文算法的有效性和鲁棒性及快速性。     

Genetic algorithms for high-precision reconstructions of three-dimensional topographies using stereo fractographs

A software is developed which enables reconstruction of the three-dimensional (3D) shape of fracture surfaces without human assistance. It is based upon computer image processing and pattern recognition techniques by using a stereo-pair of scanning electron micrographs. The processing consists of two subprocesses: searching the matching points between two images; and computation of heights using the relative shift of the matching points. By using the previously developed system, some mismatches were inevitable in the search process, in particular, for low-contrast SEM images, e.g. striations, intergranular facets, etc. In order to improve the accuracy of the search, a genetic algorithm (GA) was implemented into the developed system. By using the GA method, the 3D shapes of a wide variety of fracture surfaces including cleavage failures, intergranular cracking, dimples and fatigue striations, were successfully reconstructed with sufficient accuracy. The searching processes by the GA method and the previously developed two-step algorithm of coarse and close searching were compared. These proved that the GA method has both the advantage of accuracy in the searching process and a short run-time. A detailed 3D shape, of more than a 120 × 120 reconstructed point-sized shape, was thus obtained with sufficient accuracy and with a relatively short run-time.     

Efficient disparity estimation from stereo images using hybrid-guided image filter

Stereo vision process involves capturing the pictures from a camera of the same scene from at least two different locations and calculating the three-dimensional information. Conventionally, these two versions of snapshots are called left and right views which yield the depth information of an object upon relative comparison of its location in two views. Although the stereo image and its applications are becoming increasingly prevalent, there has been very limited research on disparity estimation from stereo images. Most of the existing techniques suffer from the gradient reversal artefacts issue. Therefore, to handle this issue, we have proposed a hybrid-guided image filter for improving the disparity estimation from stereo images. The hybrid filter utilizes the features of guided image filter and Bayesian non-local means with edge aware constraint. Maximum likelihood and local area homogeneity analysis are used to generate the guidance image for the proposed filter. To enhance the quality of disparity estimation from stereo images, segmentation is also done using the modified mean shift technique. Experimental results show that the proposed technique can efficiently estimate the depth maps over the available techniques. One-way ANOVA analysis on experimental results validates that the hybrid filter-based stereo matching outperforms consistently over the state-of-art approaches.     

Estimating the usefulness of distorted natural images using an image contour degradation measure

Quality estimators aspire to quantify the perceptual resemblance, but not the usefulness, of a distorted image when compared to a reference natural image. However, humans can successfully accomplish tasks (e.g., object identification) using visibly distorted images that are not necessarily of high quality. A suite of novel subjective experiments reveals that quality does not accurately predict utility (i.e., usefulness). Thus, even accurate quality estimators cannot accurately estimate utility. In the absence of utility estimators, leading quality estimators are assessed as both quality and utility estimators and dismantled to understand those image characteristics that distinguish utility from quality. A newly proposed utility estimator demonstrates that a measure of contour degradation is sufficient to accurately estimate utility and is argued to be compatible with shape-based theories of object perception.     

Nonlinear correlation for estimating the motion of multiple objects in image sequences

A nonlinear correlation algorithm is proposed for estimating the motion of objects from an image pair. This algorithm requires no a priori information on the number, size, or shape of the moving objects and does not require feature extraction or segmentation of either image. The algorithm directly yields information on the number of moving objects, the motion of the objects, and the size of the objects. Additional processing can be performed to yield the centroid of the objects in either frame. The utility of the resulting algorithm is demonstrated by application to a pair of example image sequences.     

Interference-based optical image encryption using three-dimensional phase retrieval

In recent years, optical image encryption has attracted more and more attention in information security due to its unique advantages, such as parallel processing and multiple-parameter characteristics. In this paper, we propose a new method using three-dimensional (3D) processing strategy for interference-based optical image encryption. The plaintext is considered as a series of particles distributed in 3D space, and any one sectional extraction cannot render information about the plaintext during image decryption. In addition, the silhouette problem in the conventional interference-based optical encryption method is effectively suppressed, and the proposed optical cryptosystem can achieve higher security compared with the previous work. A numerical experiment is conducted to demonstrate the feasibility and effectiveness of the proposed method.     

Extraction of motion parameters of gravity-wave structures from all-sky OH image sequences

We describe the application of a motion model to OH images collected by CCD cameras during three nights in February and April 1995 (3 February, 1 April, and 4 April) at the StarFire Optical Range, New Mexico. We used the instrument to take broadband images of OH Meinel bands at an altitude of 87 km to record the footprints of dynamics created by acoustic gravity waves in the mesosphere. We used the motion model to extract the velocity of the gravity waves from the images. The results of a total of 181 observations with the motion model were compared with a total of 189 observations obtained by manual estimation. We used these results to extract the intrinsic properties of the gravity waves. The mean intrinsic velocity for the three nights under consideration was 61.5 +/- 17.0 m/s with the motion model and 61.1 +/- 23.3 m/s with manual estimation.     

无缆自治水下机器人运动控制技术研究

针对无缆自治水下机器人满足不同任务要求下的运动控制进行了研究。引入极大似然参数估计算法获取水下机器人水动力系数,并在此基础上搭建起6自由度运动仿真系统。通过改进传统水下机器人体系结构中的推力器布置方式、推力分配策略、运动控制方法和船位推算算法,使得无缆自治水下机器人的运动控制系统在保持原有精确定位功能的同时也能完成远距离高速航行等任务,从而解决了高速航行给无缆自治水下机器人带来的一系列问题。海上进行的速度控制、位置控制和长航程导航试验,验证了无缆自治水下机器人在所提出的运动控制系统控制下可以满足任务需求,具有一定的工程应用价值。     

Degradation of an image by Gaussian longitudinal motion

The effect of random longitudinal motion of an image is discussed. Numerical results are given for systems with circular and annular pupils. It is shown that, for a given value of the image motion, the time-averaged Strehl ratio is larger for a larger value of the obscuration ratio of an annular pupil. We also show that the time-averaged image irradiance distribution near its center and the corresponding encircled power can be obtained from their aberration-free values by multiplying them by the Strehl ratio.     

Determination of three-dimensional displacement using two-dimensional digital image correlation

A novel method that uses a two-dimensional (2D) digital image correlation (DIC) based on a single CCD camera to measure three-dimensional (3D) displacement and deformation is proposed. Rigid-body displacement in 3D space consists of both in-plane and out-of-plane components. The presence of an in-plane displacement component results in a shift of the center of the image displacement vector, while the slope of the image displacement vector is related to the out-of-plane displacement component. Global DIC is employed to determine the displaced position of each point on an object based on a linear distribution characteristic of the displacement vector. Speckle images with deformation introduced by 3D displacement are generated to demonstrate the feasibility of the proposed method. In the 3D rigid-body displacement, both in-plane and out-of-plane displacement components are separated by determining the intercept and slope of the image displacement vector. In the 3D deformation, a zero order displacement (pure rigid-body displacement) mode is assumed in a small subset of pixels. Simulated and experimental results demonstrate that both in-plane and out-of-plane displacements can be accurately retrieved using the proposed method.     

Volume-scanning three-dimensional display that uses an inclined image plane

A novel three-dimensional display based on a volume-scanning method that uses an inclined light-source array and a mirror scanner is proposed. With this technique it is possible to display three-dimensional images that satisfy all factors for human stereoscopic vision. Three-dimensional images of 8 x 8 x 8 pixels, 40 mm x 40 mm x 40 mm in size, with a frame rate of 12.7 Hz were obtained as real images through an experimental system that uses a galvanometer mirror and a LED array.     

Effect of image resolution on intensity based scene illumination classification using neural network

In this paper, a framework for testing scene illumination classification with different image resolutions is proposed. The testing aims to provide the researchers with valuable information about the effect of image resolution on scene illumination classification using a neural network. The experiment is done by extracting three types of features from the images. These three types consist of statistical features, physic based features and histogram based features. It has been demonstrated that scene illumination classification can be affected by changing the image resolution. Despite the popular belief that high resolution images lead to better results, scene illumination classification by the proposed method performed best using low resolution images. At the second part of discussion, the reason behind this phenomenon is mathematically analysed and explained.     

医学虚拟训练的视觉与触觉场景三维同步匹配

基于高精度虚拟中国人男性一号数据集和虚拟现实开发工具Open Inventor,利用由主动式立体眼镜和力反馈设备构建的仿真平台,实现了视觉场景图和触觉场景图的三维同步匹配。论述了开发环境的具体要求,分析了视觉和触觉场景图三维同步匹配的实现策略,给出了三维同步匹配和注射模拟实验的仿真结果。结果表明,虚拟系统的视觉场景图和触觉场景图的三维同步匹配准确,可实时、快速实现视觉和触觉的立体模式医学虚拟训练。     

Determination of an optimal image frame interval for frame-to-frame ultrasound image motion tracking

Several important clinical applications depend on accurate ultrasound image frame-to-frame motion estimation. Assuming that there is a degree of finite noise in the image frames and that speckle partially decorrelates between successive frames during freehand scanning, we hypothesize that an optimal inter-frame interval (step size) must exist that provides the smallest relative dimensional error over a set of accumulated motion estimates. Smaller frame increments suffer from less decorrelation-related inaccuracy but present greater potential for cumulative error because more estimates are used over any specific dimensional interval. We studied these effects using a combination of theoretical modeling, numerical simulation, and experiments. Components of diagonal motion due to the limitations of manual transducer movement were considered as the cause of decorrelation. The results were examined for four different angles of the diagonal motion and two different signal-to-noise ratio (SNR) values. These indicate that an optimal step size does exist and that this is dependent on many variables including SNR, angle of the diagonal motion, transducer geometry, lens focusing parameters, transducer operating frequency, and beamforming parameters. In practical experiments, we found that the optimal step size generally required using every available image frame rather than 'skipping' any intermediate frames.