一种改进的窄带算法在彩色序列图像人脸跟踪中的应用

该文提出了一种基于几何主动轮廓模型的人脸跟踪方法.通过直方图反向投影,使人脸区域表现为一个一致性区域与背景相区别.研究了一种改进的窄带算法实现曲线演化:以等间隔分布的节点表示运动曲线,只在这些节点上计算Level set函数的变化值,窄带区内其余点的Level set值的更新通过插值和查表的方法实现;根据节点的局部图像信息决定节点的运动方向和时间步长值.实验表明该算法能在满足一定精度的前提下,快速地对运动人脸进行跟踪.     

Zernike moment and local distribution fitting fuzzy energy-based active contours for image segmentation

This paper presents a new region-based active contour model for extracting the object boundaries in an image, based on techniques of curve evolution. The proposed model introduces an energy functional that involves intensity distributions in local image regions and fuzzy membership functions. The local image intensity distribution information used to guide the motion of the contour, in the paper, is derived by Hueckel operator in the neighborhood of each image point. The parameters of Hueckel operator are estimated by a set of orthogonal Zernike moments before curve evolution. Meanwhile, the fuzzy membership functions are used to measure the association degree of each image pixel to the region outside and inside the contour. To minimize the energy functional, instead of solving the Euler–Lagrange equation of the underlying problem, the paper employs a direct method to compute the energy alterations. As a result, the model can deal with images with intensity inhomogeneity. In addition, the model effectively alleviates the sensitivity to contour initialization. Moreover, the model reduces computational cost, avoids problems associated with choosing time steps as well as allows fast convergence to the segmentation solutions. Experimental results on synthetic, real images and comparisons with other models show the desired performances of the proposed model.     

Segmentation and tracking in echocardiographic sequences: activecontours guided by optical flow estimates

This paper presents a method for segmentation and tracking of cardiac structures in ultrasound image sequences. The developed algorithm is based on the active contour framework. This approach requires initial placement of the contour close to the desired position in the image, usually an object outline. Best contour shape and position are then calculated, assuming that at this configuration a global energy function, associated with a contour, attains its minimum. Active contours can be used for tracking by selecting a solution from a previous frame as an initial position in a present frame. Such an approach, however, fails for large displacements of the object of interest. This paper presents a technique that incorporates the information on pixel velocities (optical flow) into the estimate of initial contour to enable tracking of fast-moving objects. The algorithm was tested on several ultrasound image sequences, each covering one complete cardiac cycle. The contour successfully tracked boundaries of mitral valve leaflets, aortic root and endocardial borders of the left ventricle. The algorithm-generated outlines were compared against manual tracings by expert physicians. The automated method resulted in contours that were within the boundaries of intraobserver variability     

A real-time algorithm for the approximation of level-set-based curve evolution.

In this paper, we present a complete and practical algorithm for the approximation of level-set-based curve evolution suitable for real-time implementation. In particular, we propose a two-cycle algorithm to approximate level-set-based curve evolution without the need of solving partial differential equations (PDEs). Our algorithm is applicable to a broad class of evolution speeds that can be viewed as composed of a data-dependent term and a curve smoothness regularization term. We achieve curve evolution corresponding to such evolution speeds by separating the evolution process into two different cycles: one cycle for the data-dependent term and a second cycle for the smoothness regularization. The smoothing term is derived from a Gaussian filtering process. In both cycles, the evolution is realized through a simple element switching mechanism between two linked lists, that implicitly represents the curve using an integer valued level-set function. By careful construction, all the key evolution steps require only integer operations. A consequence is that we obtain significant computation speedups compared to exact PDE-based approaches while obtaining excellent agreement with these methods for problems of practical engineering interest. In particular, the resulting algorithm is fast enough for use in real-time video processing applications, which we demonstrate through several image segmentation and video tracking experiments.     

引入光流法的活动轮廓模型

本文在活动轮廓模型的基础上，引入了“图象统计势能”和光流法，提出了一种新的图象分割方法，该方法改进了活动轮廓模型的一些不足，能准确地检测出物体轮廓边界，且分割结果对初始位置不敏感，同时提高了对运动速度较快的物体轮廓检测的正确性，实验结果证实了该方法的有效性。     

基于SPKFCM快速双循环水平集非均匀图像分割

针对传统快速双循环水平集对初始演化曲线过于依赖的问题,提出一种基于空间惩罚核模糊C-means (SPKFCM)算法的初始演化曲线自动选取快速双循环水平集算法.首先,对模糊均值聚类算法进行改进,通过增加空间惩罚函数提出SPKFCM算法,用于对快速双循环水平集算法的自动初始化;其次,基于SPKFCM并结合快速双循环水平集算法,设计基于SPKFCM快速双循环水平集算法框架,并给出相应速度参量Fd和Fint模糊化形式;最后,通过与已有算法在仿真图像上的对比结果显示,所提算法在随机初始化条件下,具有更高的分割精度和计算效率.     

基于变形模板技术的目标轮廓跟踪算法

为了适应目标旋转、尺度、场景光照等变化,利用B样条曲线表达目标轮廓,结合变形模板技术对运动目标的轮廓进行跟踪.在跟踪过程中,沿着模板曲线的法线方向检测目标轮廓,提高了检测效率.根据同一曲线上相邻点间的相关性,对检测所得的轮廓点集的坐标序列进行中值滤波,有效降低噪声干扰.将检测到的轮廓点集在形状空间匹配,使目标轮廓的形变限制在一定范围之内,有效抑制噪声和背景边缘特征的干扰.仿真试验表明,该算法能够有效得到目标轮廓,且具有较好的实时性.     

A multistage, optimal active contour model

Energy-minimizing active contour models or snakes can be used in many applications such as edge detection, motion tracking, image matching, computer vision, and three-dimensional (3-D) reconstruction. We present a novel snake that is superior both in accuracy and convergence speed over previous snake algorithms. High performance is achieved by using spline representation and dividing the energy-minimization process into multiple stages. The first stage is designed to optimize the convergence speed in order to allow the snake to quickly approach the minimum-energy state. The second stage is devoted to snake refinement and to local minimization of energy, thereby driving the snake to a quasiminimum-energy state. The third stage uses the Bellman (1957) optimality principle to fine-tune the snake to the global minimum-energy state. This three-stage scheme is optimized for both accuracy and speed.     

基于图像引力和Mumford-Shah模型的曲线演化算法

提出了一种图像引力和Mumford—Shah（M—S）模型的快速曲线演化算法,该算法分两步实现：首先利用图像引力,对参数主动轮廓线模型中的控制点进行寻优,使控制点能快速地收敛到图像的边缘附近;然后利用插值算法,得到目标较粗糙的大致轮廓,再使用M—S模型和窄带方法得到准确的轮廓。该算法避免了参数主动轮廓线模型不能收敛到物体凹陷的边缘和对初始位置敏感等问题,也避免了M—S模型需要对所有图像数据进行计算,计算量大等问题,实现了对参数和几何主动轮廓线模型进行了有效结合。     

基于多分辨率动态轮廓线的面积测量与跟踪方法

提出了一种基于多分辨率动态轮廓线的物体表面积测量方法。该方法使用光电式图像瞄准系统采集被测物体的目标图像并构造该图像的高斯金字塔,并采用了多分辨率动态轮廓线且使其由初始位置向目标轮廓边缘收敛;根据基于B样条封闭曲线面积与形心公式,准确计算出图像的目标面积与形心;再利用形心自标定技术、图像目标形心以及双频激光器测量出像素的尺寸当量,从而准确测量出真实物体的表面积。实验表明,在动态轮廓线控制点数目为20时,其单次测量误差达到了±0.2%。与单分辨率动态轮廓线面积测量方法相比,该方法具有鲁棒性强,平均值误差、单次测量误差及重复性误差小等优点。将该方法应用于基于红外与可见光图像融合的运动目标跟踪过程的实验表明,它不仅具有很好的跟踪准确性,而且能够跟踪快速运动的目标。     

一种全局最小化的图像分割方法

曲线活动模型是图像分割中应用广泛且成功的一类模型,但由于能量泛函的非凸构造,使得其分割结果往往陷入局部解的困境。为了克服这一点,该文在已有的曲线活动模型之一背景去除模型之上,从Heaviside函数的近似入手,提出了凸的能量泛函,并对其最小化,得到了相应的全局最小解求解方程。实验表明,该方法分割结果准确,分割速度快,具有一定的抗噪性,且对初始曲线的位置选取无特殊要求。     

基于快速水平集算法的图像分割方法

针对水平集算法计算量大,本文提出了一种使用改进的快速水平集算法的图像分割方法。本文方法是一种极限的窄带法;首先水平集的曲线进化用两个序列元素之间的交换实现;其次提出了平滑过程处理进化后的曲线;本文方法不需要解偏微分方程,运算速度很快,而且能够得到和标准算法相近的结果;实验结果证明本文算法速度快,适合于实时图像系统中的应用。     

Validation of an optical flow method for tag displacementestimation

We present a validation study of an optical-flow method for the rapid estimation of myocardial displacement in magnetic resonance tagged cardiac images. This registration and change visualization (RCV) software uses a hierarchical estimation technique to compute the flow field that describes the warping of an image of one cardiac phase into alignment with the next. This method overcomes the requirement of constant pixel intensity in standard optical-flow methods by preprocessing the input images to reduce any intensity bias which results from the reduction in stripe contrast throughout the cardiac cycle. To validate the method, SPAMM-tagged images were acquired of a silicon gel phantom with simulated rotational motion. The pixel displacement was estimated with the RCV method and the error in pixel tracking was <4% 1000 ms after application of the tags, and after 30 degrees of rotation. An additional study was performed using a SPAMM-tagged multiphase slice of a canine left ventricle. The true displacement was determined using a previously validated active contour model (snakes). The error between methods was 6.7% at end systole. The RCV method has the advantage of tracking all pixels in the image in a substantially shorter period than the snakes method.     

Towards multi-stage texture-based active contour image segmentation

In this paper, we present a three-stage approach to incorporation of texture analysis into a two-dimensional active contour segmentation framework. This approach allows to utilise texture information alongside other image features. The proposed method starts with an initial unsupervised feature computation and selection, then moves to a fast contour evolution process and ends with a final refinement stage. The algorithm is designed to be general in its nature and not restricted to any particular texture feature extraction method. In this paper, the initial stage generates a set of feature maps consisting of grey-level co-occurrence matrix and Gabor features. The implementation makes an extensive use of hardware acceleration for efficient calculation of a relatively large number of features. The performance of the method was tested on various synthetic and natural images and compared with results of other algorithms.     

应用于流水线模数转换器的快速前后台组合数字校正

本文描述了一种用于流水线模数转换器的快速数字校正技术。所提出的数字校正方法利用了前台和后台校正,可以纠正由于MDAC中电容失配和运放有限增益所产生的非线性。在本文的组合校正算法中,提出了新型带有信号平移相关算法的并行数字后台校正技术,它的校正周期非常短。本文的数字校正方法以一个14位100Msps流水线模数转换器为例。本文的数字后台校正通过三种方式达到高速的收敛速度。首先,提出了改进型1.5位流水线子级,目的是在信号通路中注入大幅值的伪随机抖动信号而不产生失码;其次,在校正级输出信号进行相关运算之前先根据校正级的输入信号范围进行平移,从而使相关运算达到高速的收敛速度;最后,前端流水线子级同时进行校正,而不是逐级进行校正,从而降低数字后台校正周期。仿真结果证明组合校正具有快速的启动过程和非常短的后台校正周期。     

一种改进的红外弱小目标快速检测方法

针对复杂背景下红外弱小目标检测率低、目标跟踪困难的问题,提出一种改进的红外弱小目标快速检测方法。该方法采用改进的形态学滤波抑制背景噪声,对处理后的多帧图像进行方差估计初步突出目标像素,然后对其进行信噪比估计得到整个图像序列像素得分,图像中像素信噪比高的被标记为目标像素,再对标记过的图像进行分块分析,最终准确提取出连续图像序列中的目标像素。检测出的目标像素作为Hough变换的目标跟踪算法的输入,设置双阈值实现目标的有效跟踪。实验结果表明,在复杂背景下的红外弱小目标提取中,基于噪声方差估计的目标检测拥有较高的检测概率和较低的虚警概率,将其获得的目标像素作为Hough变换的输入,不仅可以有效跟踪目标,而且简化了算法的复杂度,实现目标的快速提取和跟踪,具有很高的应用价值。     

A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations

In this paper, we develop a novel region-based approach to snakes designed to optimally separate the values of certain image statistics over a known number of region types. Multiple sets of contours deform according to a coupled set of curve evolution equations derived from a single global cost functional. The resulting active contour model, in contrast to many other edge and region based models, is fully global in that the evolution of each curve depends at all times upon every pixel in the image and is directly coupled to the evolution of every other curve regardless of their mutual proximity. As such evolving contours enjoy a very wide “field of view,” endowing the algorithm with a robustness to initial contour placement above and beyond the significant improvement exhibited by other region based snakes over earlier edge based snakes.     

A curve evolution approach to object-based tomographic reconstruction

We develop a new approach to tomographic reconstruction problems based on geometric curve evolution techniques. We use a small set of texture coefficients to represent the object and background inhomogeneities and a contour to represent the boundary of multiple connected or unconnected objects. Instead of reconstructing pixel values on a fixed rectangular grid, we then find a reconstruction by jointly estimating these unknown contours and texture coefficients of the object and background. By designing a new "tomographic flow", the resulting problem is recast into a curve evolution problem and an efficient algorithm based on level set techniques is developed. The performance of the curve evolution method is demonstrated using examples with noisy limited-view Radon transformed data and noisy ground-penetrating radar data. The reconstruction results and computational cost are compared with those of conventional, pixel-based regularization methods. The results indicate that the curve evolution methods achieve improved shape reconstruction and have potential computation and memory advantages over conventional regularized inversion methods.     

序列帧间双重匹配的红外点目标跟踪算法

针对海空复杂背景下红外点目标的检测与跟踪,提出了基于图像序列帧间双重匹配的边跟踪边检测算法,并建立了数学模型。它采用标记序列帧M以帧对帧的方式记录输入序列的帧间匹配结果,标记帧T以点对点的方式记录标记序列帧M的帧间匹配结果,统计帧S记录T中各像素的匹配成功次数,输入单帧图像同步输出矩阵T和S分别显示目标运动轨迹和迎头目标检测结果。算法匹配过程不随目标数目或运动状态而改变,且无需提前判断疑似目标位置,有效解决了目标在图像序列中突然丢失或出现被干扰情况下的跟踪,尤其可以对跟踪结果实时地进行目标分离,解决了迎头目标跟踪的难题。仿真和实际工程图像实验结果表明,算法具有较高的可靠性和实时性。     

Contour simplification and motion compensated coding

In order to solve the bottleneck problem of region-based coding scheme, which is the contour coding, lossy methods are introduced in this paper for both 2D and 3D (2D plus time) contour image(s). A non-linear filter by means of majority operation is designed to act as contour simplification for both pre-processing and post-processing of contour coding. An average of 20% gain in contour coding cost is achieved by using this filter while the contour location error is controlled within one pixel width. Afterwards, an efficient contour motion estimation and compensated coding method are presented. In order to exploit the high temporal redundancy of the contour image sequence, motion estimation and compensation are applied to the correspondent label image sequence. First frame is directly coded by Chain-code method. All the following frames are coded in motion compensated mode. Meanwhile, a fast implementation of full search motion estimation algorithm is also described. This algorithm is 2R times faster than traditional method (R is the total regional number). Within each frame, labels are divided into foreground labels and background labels. Only the noticeable prediction errors for the foreground labels are coded. Morphological filters are used to clean the prediction errors of the foreground labels. An efficient prediction error coding algorithm is then introduced based on one-side Chain-code method. The reconstruction of foreground and background regions in the decoder side is also described. Experimental results have demonstrated good performance for very low bitrate video coding applications.