Simultaneous surface area measurement for multiple objects by geodesic active contour

A novel scheme to the area measurement of multiple objects is proposed. This scheme is suitable for the simultaneous and exact measurement of multiple objects’ surface areas with different shapes. A geodesic active contour is applied and this scheme consists of three steps. Firstly, the active contour converges to the object's contour edge from an initial position via the iteration of level set functional ?. Secondly, for the convergent active contour, the sub-pixel area measurement and centroid measurement are applied to compute every object's area and centroid simultaneously. Finally, a centroid-self-calibration technology is applied, which measures the pixel's size equivalence with the computed centroid and a dual-frequency laser to measure every object's true surface area. Experiments indicate that this scheme's measurement repetition error can decrease to ±0.4% and that its single measurement error can decrease to ±0.2%. Compared to conventional area measurement schemes, this scheme is highly efficient (i.e., simultaneous measurement of multiple objects’ areas) and highly accurate.     

Simultaneous perimeter measurement for multiple planar objects

A novel scheme to measure the true boundary perimeters of multiple planar objects is proposed. This scheme is suitable for the simultaneous and accurate measurement of multiple objects’ boundary perimeters with different shape. A geodesic active contour is applied and this scheme consists of three steps. First, the active contour converges to the object's contour edge from an initial position via the iteration of the level set functional . Second, for the convergent active contour, the sub-pixel edge detection and the centroid measurement are applied to obtain every object's edge and centroid coordinate simultaneously. Finally, a centroid-self-calibration technology is applied, which measures the pixel's size equivalence with the computed centroid and a dual-frequency laser to measure every object's true boundary perimeter. Experiments indicate that this scheme's measurement repetition error decreases to ±0.4% and that its single measurement error decreases to ±0.2%. Compared to conventional perimeter measurement schemes, this scheme is highly efficient (i.e., simultaneous measurement of multiple objects’ boundary perimeters) and highly accurate.     

Precise perimeter measurement for 3D object with a binocular stereo vision measurement system

A novel measurement scheme for a three dimensional (3D) object's surface boundary perimeter is proposed. This scheme consists of three steps. First, a binocular stereo vision measurement system with two CCD cameras is devised to obtain the two images of a detected object's 3D surface boundary. Second, two B-spline active contours are applied to converge to the object's contour edges accurately in the two CCD images to perform the stereo matching. Finally, for the reconstructed 3D active contour, its true contour length is computed as the detected object's true boundary perimeter. An experiment on a bent surface's perimeter measurement indicates that this scheme's measurement repetition error decreases to 0.6%.     

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%。     

Image-fusion-based multi-resolution active contour model

This paper proposes an active contour model (snake) based on image fusion, which is used in object detection and object tracking. Firstly, a multi-resolution image fusion with wavelet transform is applied to obtain the multi-resolution fused images. Secondly, in the low-frequency sub-image, a snake is applied with the Sobel operator to detect the object's contour; and in other high-frequency sub-images, a wavelet-based snake is applied. The two convergent snakes are fused in a multi-resolution scheme to obtain a fused snake in the fused image in an original resolution. Experiment results indicate this fused snake's detection or tracking accuracy is improved greatly.     

基于图像融合的动态轮廓线跟踪新方法

红外与可见光传感器是目标跟踪识别系统中常用的两种传感器,对这两种传感器图像进行融合能有效提高系统跟踪检测的准确性。将动态轮廓线模型与图像融合结合,在特征搜索过程中利用特征点准确地完成了图像配准,同时使用了一种新的特征级融合方法,将两种图像中目标轮廓的B样条曲线控制点进行实时微分耦合。这种耦合将Curwen提出的微分耦合机制作了改进,利用图像配准把刚性硬模板改变为实时的变换模板并推导了融合后动态轮廓线的新的动力学方程。这种融合利用了红外图像目标轮廓信息约束可见光图像中动态轮廓线的收敛形状,有效地提高了可见光图像目标跟踪的准确性。对运动人手序列图像的对比跟踪实验表明,这种融合使得可见光图像中动态轮廓线平均跟踪误差减小了60．25％。     

基于序列图像的运动目标检测

针对动态环境下运动目标检测中噪声多、目标检测不完整等情况,提出了一种基于金字塔多分辨率模型的运动目标检测方法,在低分辨率下获取目标的区域,在高分辨率下获取目标的细节。对于复杂的环境,还提出了运用高低双阈值替代传统的单阈值进行图像差分运算的方案,阈值可以根据图像自动分析得到。该方法首先将当前帧和背景帧进行尺度变换,得到不同分辨率下的图像组,然后在不同尺度下得到高低阈值差分图像,最后从高层向低层进行有效融合,得到噪声少的完整目标图像。实验表明,该方法提取运动目标的精度比较高,单目标达到0.802,多目标达到0.615,尤其是在复杂的动态环境下,优势比较明显。     

基于形态学4子带分解金字塔的图像融合

提出了一种基于数学形态学滤波的多分辨力图像融合。这种融合方法使用了形态学开闭运算构造了低通与高通滤波器,将原始图像分解为4子带图像金字塔和4子带方向衬比度图像金字塔。然后利用方向衬比度和区域标准差进行图像融合得到融合的4子带图像金字塔,最后应用子带图像重构得到融合图像。融合实验表明,该方法优于传统的形态学金字塔图像融合,衬比度金字塔图像融合和小波分解图像融合。     

基于红外图像的GVF Snake轮廓提取算法的研究

针对红外图像目标具有边界模糊不清,区分效果较差的缺点,结合Ostu阈值法和梯度矢量流主动轮廓模型（GVF Snake）,提出一种目标轮廓自动提取方法。采用Ostu法先对图像进行分割,然后将得到的边界作为Snake模型的初始边缘轮廓,利用 GVF Snake特性将初始轮廓准确地收敛到目标边界。由于Ostu算法具有将目标物体从复杂背景中分割开来的优点,使得在应用 GVF Snake模型对复杂图像进行分割时减少了人工的干预。实验证明：该方法运算速度快,能够快速地收敛到目标轮廓,并准确地跟踪目标,具有一定的抗噪能力。     

Vehicle speed measurement based on gray constraint optical flow algorithm

Vehicle speed measurement (VSM) based on video images represents the development direction of speed measurement in the intelligent transportation systems (ITS). This paper presents a novel vehicle speed measurement method, which contains the improved three-frame difference algorithm and the proposed gray constraint optical flow algorithm. By the improved three-frame difference algorithm, the contour of moving vehicles can be detected exactly. Through the proposed gray constraint optical flow algorithm, the vehicle contour's optical flow value, which is the speed (pixels/s) of the vehicle in the image, can be computed accurately. Then, the velocity (km/h) of the vehicles is calculated by the optical flow value of the vehicle's contour and the corresponding ratio of the image pixels to the width of the road. The method can yield a better optical flow field by reducing the influence of changing lighting and shadow. Besides, it can reduce computation obviously, since it only calculates the moving target contour's optical flow value. Experimental comparisons between the method and other VSM methods show that the proposed approach has a satisfactory estimate of vehicle speed.     

水下目标物偏振成像特性研究

偏振图像比传统强度图像包含更丰富的物体表面反射及散射信息。用萨尔萨(SALSA)相机在自然光照下获取水下偏振图像，研究不同材质物体、放置深度、牛奶浓度及波段因素对水下目标物偏振成像的影响。结果表明:蓝色波段偏振成像能够较好地获取水下物体的边界轮廓等信息; 不同材质的目标物在水下呈现不同的偏振特性, 紫铜偏振度最高达0.69;在1.40 mg/L牛奶浑浊度的水下，偏振图像仍能通过比较目标物的偏振度(degree of polarization，DOP)信息来检测出水下目标物，瓷片的DOP仅降低0.31;此外，在水下约40 cm深度下，偏振成像获取的图像比强度图像轮廓更为清晰，如铁的偏振对比度比强度对比度高5.26%。     

Feature-based fusion of infrared and visible dynamic images using target detection

We employ the target detection to improve the performance of the feature-based fusion of infrared and visible dynamic images, which forms a novel fusion scheme. First, the target detection is used to segment the source image sequences into target and background regions. Then, the dual-tree complex wavelet transform (DT-CWT) is proposed to decompose all the source image sequences. Different fusion rules are applied respectively in target and background regions to preserve the target information as much as possible. Real world infrared and visible image sequences are used to validate the performance of the proposed novel scheme. Compared with the previous fusion approaches of image sequences, the improvements of shift invariance, temporal stability and consistency, and computation cost are all ensured.     

基于航迹和特征的目标识别技术在多目标跟踪中的应用

针对目前机动目标跟踪所面临的机箭分离、机弹分离、级间分离等一转多的目标跟踪问题,提出了一种复合目标识别技术.针对目标的面积,外接矩形长度、宽度、长宽比,紧凑度,转动惯量和航迹对多种目标进行准确的认定和匹配,并在目标的切换过程中引入一种新型切换技巧.此算法大大提高了一转多目标的跟踪可靠性,实际应用表明:目标识别准确,跟踪切换平稳,应用价值高.     

Moving target detection approach based on spatio-temporal salient perception

The differences in texture and motion between man-made object and natural scene are the key features for human biological visual system to detect moving object in scenery. The paper proposed a moving target detection approach based on spatio-temporal perception, which is a crucial function of the visual attention mechanism. The spatial feature including edge, orientation, texture and contrast of the image are extracted, and then the corresponding spatial salient map are constructed by fusing the features through difference of Gaussian (DOG) function, which can suppress the common and enhance the difference of local region. Then, the global motion, local motion and relative motion between continuous images are extracted by means of pyramid multi-resolution, and the moving salient map is constructed after the motion difference between moving target and background is confirmed. Finally, the spatio-temporal salient map is constructed by fusing the spatial salient map and the moving salient map through competition strategy, and the moving target could be detected by searching the maximum in the spatio-temporal salient map. Some experiments are included and the results show that the method can accurately detect the moving target in complex background.     

基于阈值判断的CamShift目标跟踪算法

针对CamShift算法只利用目标的颜色信息,在跟踪过程中,易受目标相似物、遮挡以及光照等复杂背景影响导致目标搜索窗口发散,跟踪稳定性能降低,提出了一种基于阈值判断的目标跟踪方法。该方法将OTSU法和Snake模型结合,利用OTSU法以最佳阈值对图像进行分割,分离前景区域和背景区域,初步提取目标轮廓作为Snake模型的初始轮廓,经收敛得到目标的精准轮廓,利用轮廓外接最小矩形框内的像素计算目标质心,判断与CamShift算法中目标搜索窗口质心之间的欧式距离,如果未超出阈值,则直接使用CamShift算法跟踪目标,反之,则将计算出的目标质心作为CamShift算法中当前帧目标搜索窗口的质心跟踪目标。实验结果表明,该算法跟踪目标具有较好的实时性,跟踪性能稳定、可靠。     

Several factors impairing the phase measurement accuracy

In the course of processing deformed grating patterns and obtaining an object's height distribution with a digital filter, several factors, such as dynamic and frequency ranges of phase signal, background luminance and reflection coefficient of the measured object, grating period, filter passband, time drift of image data, etc., may exert an influence on the phase measurement accuracy. Through simulation and experiment, the influence is discussed and the conclusion is that, by choosing a suitable grating period and filter frequency characteristic according to the frequency range of the phase signal, the phase measurement error will be reduced.     

基于多小波变换的红外目标探测与识别

针对光电联合变换相关器目标识别的实际应用,对待测红外目标图片进行多小波变换,并利用模极大值法提取其边缘.通过获取更多的轮廓信息,从而提高对目标的识别能力.计算机模拟了常用于红外目标处理的多小波GHM和SA4,实验结果表明:基于GHM多小波提取的边缘能获取大量的图像轮廓信息,其识别结果明显优于SA4多小波.将目标原图的光学相关探测结果与基于GHM多小波提取的边缘图像光学相关探测结果进行比较发现,经多小波预处理后的边缘图像能有效增强相关峰强度.     

Precise speed measurement using an interlaced scan image

In this paper, we propose a novel scheme for speed measurement of a moving object with translational motion. First, this scheme uses one interlaced scan CCD camera to obtain only one interlaced scan image of a moving object. The odd and even field images are extracted and resized. Second, image matte is applied in these two field images to extract the moving object’s silhouettes. The distance between two centroids in the two silhouettes is then computed. Finally, the object’s speed is calculated using the above distance and the camera imaging parameters. Simulation and real experiments prove that our scheme can fulfill the speed measurement for translational motion accurately.