An automated method for lumen and media-adventitia border detection in a sequence of IVUS frames

In this paper, we present a method for the automated detection of lumen and media-adventitia border in sequential intravascular ultrasound (IVUS) frames. The method is based on the use of deformable models. The energy function is appropriately modified and minimized using a Hopfield neural network. Proper modifications in the definition of the bias of the neurons have been introduced to incorporate image characteristics. A simulated annealing scheme is included to ensure convergence at a global minimum. The method overcomes distortions in the expected image pattern, due to the presence of calcium, employing a specialized structure of the neural network and boundary correction schemas which are based on a priori knowledge about the vessel geometry. The proposed method is evaluated using sequences of IVUS frames from 18 arterial segments, some of them indicating calcified regions. The obtained results demonstrate that our method is statistically accurate, reproducible, and capable to identify the regions of interest in sequences of IVUS frames.     

突发通信中基于叠加训练的信道估计方案

针对无线突发通信中频带利用率低、信道参数获取困难等问题,提出了一种应用于突发通信的叠加训练信道估计与检测方案。该方案将信息和训练叠加发送,通过预失真发送信息符号使得训练与信息在频域正交,收端采用一阶统计信道估计和最大似然符号检测,并设计了抗直流干扰的信道估计方案。仿真表明,新方案在消除训练序列的频带开销的情况下获得了较好的信道估计和符号检测性能,与采用时分复用训练的方案相比,其有效吞吐率更优。     

基于局部形状结构分类的心血管内超声图像中-外膜边界检测

本文提出了一种基于局部形状结构分类的心血管内超声（Intravascular Ultrasound,IVUS）图像中-外膜边界检测方法.首先利用k-均值（k-means）聚类方法,确定局部形状结构类别;其次通过类别标号索引图像块,并对其进行积分通道特征和自相似性特征提取,构建多分类随机决策森林模型;最后由分类模型寻找IVUS图像的关键点,采用曲线拟合方法,实现IVUS图像中-外膜边界检测.实验结果表明,本文方法能够有效地解决IVUS图像中斑块、伪影和血管分支等造成边缘难以准确检测的问题,与已有算法相比,其JM （Jaccard Measure,JM）达到了88.9%,PAD （Percentage of Area Difference,PAD）降低了19.1%,HD （Hausdorff Distance,HD）减少了9.7%,更准确地识别目标边界的关键点,成功地检测出完整的中-外膜边界.     

基于叠加训练的非合作多用户/MIMO信道估计

提出一种基于叠加训练的单载波非合作多用户/MIMO系统的迭代信道估计与检测方案。首先利用变换域方法构造具有零周期互相关特性的训练序列,从而消除多天线间的相互干扰,实现基于一阶统计量的信道估计。然后采用联合符号检测的迭代信道估计方法,利用检测序列作为额外的“训练序列”来降低信息序列自身干扰。与现有的叠加训练信道估计方案比较,新方案中训练序列构造更加灵活,在低信噪比下信道估计均方误差和误码率性能更优,且复杂度更低,仿真结果表明了该方案的有效性。     

A robust 3-D IVUS transducer tracking using single-plane cineangiography

During an intravascular ultrasound (IVUS) intervention, a catheter with an ultrasound transducer is introduced in the body through a blood vessel, and then, pulled back to image a sequence of vessel cross sections. Unfortunately, there is no 3-D information about the position and orientation of these cross-section planes, which makes them less informative. To position the IVUS images in space, some researchers have proposed complex stereoscopic procedures relying on biplane angiography to get two X-ray image sequences of the IVUS transducer trajectory along the catheter. To simplify this procedure, we and others have elaborated algorithms to recover the transducer 3-D trajectory with only a single view X-ray image sequence. In this paper, we present an improved method that provides both automated 2-D and 3-D transducer tracking based on pullback speed as a priori information. The proposed algorithm is robust to erratic pullback speed and is more accurate than the previous single-plane 3-D tracking methods.     

On-board selection of relevant images: an application to linearfeature recognition

We propose an on-board selection scheme for aerial and space images, based on linear feature detection in a feature hyperspace. The detection task is performed by means of the Radon transform (RT) and the wavelet transform; a fast algorithm for the RT computation is described, and counteractions against the discretization errors are proposed. A new, wavelet-based algorithm is introduced, which performs a fine analysis of the waveforms of the RT peaks, yielding a possibly error-free detection in images corrupted by a high level of noise. A technique, based on the feature hyperspace, is proposed, able to significantly exploit all the available pieces of information on these peaks. Results of the tests on synthetic and real images are reported, which show that this method achieves satisfactory results, making the detection task highly reliable in the presence of both noise and clutter.     

时空深度特征AP聚类的稀疏表示视频异常检测算法

针对异常行为检测问题, 提出基于时空深度特征的AP聚类稀疏表示视频异常检测方法。由于视频序列中大量背景信息及有效信息分布不均匀的情况，首先利用光流结合非均匀的细胞分割对视频的运动目标进行提取并得到空间尺寸大小不同的时空兴趣块。其次利用三维卷积神经网络提取不同时空兴趣块的时空深度特征从而对原始视频序列进行三维描述。然后在字典学习时，采用AP聚类方法，将训练样本中具有代表性的特征作为字典，极大降低字典维度以及稀疏表示方法对计算内存的要求。本文将测试样本进行AP聚类后仅对具有代表性的聚类中心进行检测，在减少实验时间的同时削减了阈值对检测效果的敏感度。实验结果表明，与现有的检测方法相比本文方法具有优越性。      

基于自适应色彩聚类和上下文信息的自然场景文本检测

自然场景文本检测是图像内容分析和理解的重要前提.本文提出一种基于自适应色彩聚类和上下文信息分析的方法,用于检测自然场景图像文本.首先,将层次聚类和参数自学习策略结合,设计一种自适应色彩聚类方法,提取图像中的候选字符.该自适应色彩聚类方法能针对不同图像自动学习权重阈值,有较好的字符召回率.然后,利用文本中字符成行出现的性质,设计一种基于上下文信息的字符验证策略,既能保证较高字符召回率,也能有效移除非文本字符.最后,合并字符构建文本行,并通过后处理得到文本检测结果.在ICDAR2013公共数据集上的实验结果表明：本文分别获得74.17%的召回率,83.40%的准确率和78.52%的F得分.与其他文本检测方法相比,本文获得了较好的文本检测性能,说明本文方法的优越性.     

An effective SVD-based image tampering detection and self-recovery using active watermarking

In this paper, an effective tamper detection and self-recovery algorithm based on singular value decomposition (SVD) is proposed. This method generates two distinct tamper detection keys based on the singular value decomposition of the image blocks. Each generated tamper detection and self-recovery key is distinct for each image block and is encrypted using a secret key. A random block-mapping sequence and three unique optimizations are employed to improve the efficiency of the proposed tamper detection and the robustness against various security attacks, such as collage attack and constant-average attack. To improve the proposed tamper localization, a mixed block-partitioning technique for 4×4 and 2×2 blocks is utilized. The performance of the proposed scheme and its robustness against various tampering attacks is analyzed. The experimental results demonstrate that the proposed tamper detection is superior in terms of tamper detection efficiency with a tamper detection rate higher than 99%, security robustness and self-recovery image quality for tamper ratio up to 55%.     

Detection of rapid-eye movements in sleep studies

One of the key features of rapid-eye movement (REM) sleep is the presence of bursts of REMs. Sleep studies routinely use REMs to classify sleep stages. Moreover, REM count or density has been used in studies involving learning and various psychiatric disorders. Most of these studies have been based on the visual identification of REMs, which is generally a very time-consuming task. This and the varying definitions of REMs across scorers have warranted the development of automatic REM detection methodologies. In this paper, we present a new detection scheme that combines many of the intrinsic properties of REMs and requires minimal parameter adjustments. In the proposed method, a single parameter can be used to control the REM detection sensitivity and specificity tradeoff. Manually scored training data are used to develop the method. We assess the performance of the method against manual scoring of individual REM events and present validation results using a separate data set. The ability of the method to discriminate fast horizontal ocular movement in REM sleep from other types of events is highlighted. A key advantage of the presented method is the minimal a priori information requirement. The results of training data (recordings from five subjects) show an overall sensitivity of 78.8% and specificity of 81.6%. The performance on the testing data (recording from five subjects different from the training data) showed overall sensitivity of 67.2% and specificity of 77.5%.     

Automatic detection and quantification of tree-in-bud (TIB) opacities from CT scans

This study presents a novel computer-assisted detection (CAD) system for automatically detecting and precisely quantifying abnormal nodular branching opacities in chest computed tomography (CT), termed tree-in-bud (TIB) opacities by radiology literature. The developed CAD system in this study is based on 1) fast localization of candidate imaging patterns using local scale information of the images, and 2) M?bius invariant feature extraction method based on learned local shape and texture properties of TIB patterns. For fast localization of candidate imaging patterns, we use ball-scale filtering and, based on the observation of the pattern of interest, a suitable scale selection is used to retain only small size patterns. Once candidate abnormality patterns are identified, we extract proposed shape features from regions where at least one candidate pattern occupies. The comparative evaluation of the proposed method with commonly used CAD methods is presented with a dataset of 60 chest CTs (laboratory confirmed 39 viral bronchiolitis human parainfluenza CTs and 21 normal chest CTs). The quantitative results are presented as the area under the receiver operator characteristics curves and a computer score (volume affected by TIB) provided as an output of the CAD system. In addition, a visual grading scheme is applied to the patient data by three well-trained radiologists. Interobserver and observer-computer agreements are obtained by the relevant statistical methods over different lung zones. Experimental results demonstrate that the proposed CAD system can achieve high detection rates with an overall accuracy of 90.96%. Moreover, correlations of observer-observer (R(2)=0.8848, and observer-CAD agreements (R(2)=0.824, validate the feasibility of the use of the proposed CAD system in detecting and quantifying TIB patterns.     

Moving object detection and tracking from video captured by moving camera

This paper presents an effective method for the detection and tracking of multiple moving objects from a video sequence captured by a moving camera without additional sensors. Moving object detection is relatively difficult for video captured by a moving camera, since camera motion and object motion are mixed. In the proposed method, the feature points in the frames are found and then classified as belonging to foreground or background features. Next, moving object regions are obtained using an integration scheme based on foreground feature points and foreground regions, which are obtained using an image difference scheme. Then, a compensation scheme based on the motion history of the continuous motion contours obtained from three consecutive frames is applied to increase the regions of moving objects. Moving objects are detected using a refinement scheme and a minimum bounding box. Finally, moving object tracking is achieved using a Kalman filter based on the center of gravity of a moving object region in the minimum bounding box. Experimental results show that the proposed method has good performance.     

An automatic approach for artifacts detection and shadow enhancement in intravascular ultrasound images

Intravascular ultrasound (IVUS) is clinically available for visualizing coronary arteries. However, it suffers from acoustic shadow areas and ring-down artifacts as two of the common issues in IVUS images. This paper introduces an approach which can overcome these limitations. As shadow areas were displayed behind hard plaques in the IVUS grayscale images, calcified plaques were first segmented by using Otsu threshold. Then, active contour, histogram matching, and local histogram matching are implemented. In addition, a new modified circle Hough transform is introduced to remove the ring-down artifacts from IVUS images. In order to evaluate the efficacy of this new method in detection of shadow and ring-down regions, 300 IVUS images are considered. Sensitivity of 89% and specificity of 92% are achieved from a comparison in revelation of calcium along with shadow in the proposed method and virtual histology images. Also, area differences of \(5.83 \pm 3.3\) and \(5.65 \pm 2.83\) are obtained, respectively, for ring-down and shadow domain when compared to measures performed manually by a clinical expert.     

一种基于MIMO-FSO的最大似然盲检测算法

在多天线自由空间无线光通信(MIMO-FSO)系统中,提出一种基于通用最大似然的序列(MLSD)盲检测算法,使用等增益合并(EGC)获得MIMO空间分集,研究了大气湍流衰落信道不同强度条件下算法的性能。此外,针对MLSD在较长序列长度下的高复杂度,提出一种次优的快速搜寻算法。蒙特卡洛仿真结果显示,所提出的接收机模型在MIMO-FSO系统中,能够获得空间分集,在不同信道条件、中等序列长度条件下,得到接近最优检测的性能。     

红外背景抑制与小目标检测算法

在有云层背景的红外序列图像中,检测和跟踪微弱小目标一直是研究的重点。介绍了一种简单可行的在云层背景下检测小目标的方案。算法中,首先进行背景抑制以获得更高的信噪比,接着是用门限分割以得到二值图像,最后依照目标在时间和空间运动的连续性,用一种管线法进行目标识别。实验结果表明算法十分有效。     

Diversity coding scheme for wireless optical communication with direct detection

A new diversity coding scheme using four transmit apertures, one receive aperture and two detectors is proposed for wireless optical communication with direct detection. Pilot symbols are inserted to the encoding information sequence. Simulations show that the scheme can yield a signal-to-noise ratio gain of 6 dB at 10/sup -4/ error probability.     

基于FM0记忆辅助特性的RFID标签碰撞检测

为实现两个射频识别(RFID)碰撞标签信息的检测和分离,提出一种利用Gen2标准中FM0标签编码固有记忆特性的检测方法。通过对FM0比特编码特点和碰撞标签信息的无记忆检测分析,得到基于单个比特持续时间的无记忆检测方法的条件错误概率和单个标签信息检测的误码率;然后利用单个FM0比特编码需要前一比特的“记忆”特性,得到对应于前一比特的一对测量值和对应于下一比特的一对测量值,进而得到碰撞标签信息的1比特记忆辅助检测时的条件错误概率和误码率性能;并对在帧Aloha媒质接入方案中采用提出的检测方法时的N个标签群的总延迟减少性能进行了分析。仿真实验结果表明,提出的1比特记忆辅助检测方法,相比于无记忆检测具有更好的误码率性能,且能减少标签群接入时的总延迟。     

一种图像的隐藏信息还原方法

提出了一种基于遗传算法的机密信息还原方法.该方法首先确定嵌入扩频序列的长度:然后,采用遗传算法求得嵌入序列的最佳估计:进而,用最佳的估计序列还原出机密信息.实现机密信息的盲还原.该方法己在微机上进行模拟实验,实验结果表明,还原效果较好.     

微弱信号检测的变尺度Duffing振子方法

针对强噪声背景下微弱信号检测问题,本文把互补集总经验模式分解（CEEMD）方法和变尺度Duffing振子结合,提出了一种新的微弱信号检测方法.利用CEEMD将复杂含噪信号分解为不同的固有模态函数（IMF）,通过Duffing系统分岔图及其变化找到相轨迹变化的临界阈值,实现含噪信号的信息检测.结果表明,本文所提方法不仅可以很好地免疫噪声,而且能有效检测出信噪比低至-73dB的多频率周期信号.     

Efficient multiple moving object detection and tracking using combined background subtraction and clustering

Object detection and tracking is a fundamental, challenging task in computer vision because of the difficulties in tracking. Continuous deformation of objects during movement and background clutter leads to poor tracking. In this paper, a method of multiple moving object detection and tracking by combining background subtraction and K-means clustering is proposed. The proposed method can handle objects occlusion, shadows and camera jitter. Background subtraction filters irrelevant information, and K-means clustering is employed to select the moving object from the remaining information, and it is capable of handling merging and splitting of moving objects using spatial information. Experimental results show that the proposed method is robust when compared to other techniques.