数字电影发行相似案例快速检索方法

为解决传统相似案例检索方法在数字电影大型案例库中检索效率低下的问题,针对数字电影大型案例库进行了研究分析,从提高案例检索速度和参考价值的角度出发,提出了一种聚类、优选和匹配相结合的相似案例检索方法.通过聚类缩小案例的检索范围,通过优选在相应的检索范围内形成参考价值较高的候选案例集,通过匹配算法在候选案例集中寻找最相似案...     

Efficient retrieval of similar shapes

We propose an indexing technique for the fast retrieval of objects in 2D images based on similarity between their boundary shapes. Our technique is robust in the presence of noise and supports several important notions of similarity including optimal matches irrespective of variations in orientation and/or position. Our method can also handle size-invariant matches using a normalization technique, although optimality is not guaranteed here. We implemented our method and performed experiments on real (hand-written digits) data. Our experimental results showed the superiority of our method compared to search based on sequential scanning, which is the only obvious competitor. The performance gain of our method increases with any increase in the number or the size of shapes. Edited by W. Klas. Received: 10 February 2000 / Accepted: 9 July 2001 / Published online: 15 February 2002 –     

Optimal configurations for peer-to-peer user-private information retrieval

User-private information retrieval systems should protect the user’s anonymity when performing queries against a database, or they should limit the servers capacity of profiling users. Peer-to-peer user-private information retrieval (P2P UPIR) supplies a practical solution: the users in a group help each other in doing their queries, thereby preserving their privacy without any need of the database to cooperate. One way to implement the P2P UPIR uses combinatoric configurations to administrate the keys needed for the private communication between the peers.This article is devoted to the choice of the configuration in this system. First of all we characterize the optimal configurations for the P2P UPIR and see the relationship with the projective planes as described in finite geometry. Then we give a very efficient construction of such optimal configurations, i.e. finite projective planes. We finally check that the involved graphs are Ramanujan graphs, giving an additional justification of the optimality of the constructed configurations.     

Mammogram retrieval on similar mass lesions

Enormous numbers of digital mammograms have been produced in hospitals and breast screening centers. To exploit those valuable resources in aiding diagnoses and research, content-based mammogram retrieval systems are required to effectively access the mammogram databases. This paper presents a content-based mammogram retrieval system, which allows medical professionals to seek mass lesions that are pathologically similar to a given example. In this retrieval system, shape and margin features of mass lesions are extracted to represent the characteristics of mammographic lesions. To compare the similarity between the query example and any lesion within the databases, this study proposes a similarity measure scheme which involves the hierarchical arrangement of mammographic features and a weighting distance measure. This makes similarity measure of the retrieval system consistent with the way radiologists observe mass lesions. This study used the DDSM dataset to evaluate the effectiveness of the extracted shape feature and margin feature, respectively. Experimental results demonstrate that, when Zernike moments are used, round-shape masses are the most discriminative among four types of shape; the circumscribed-margin masses can be effectively discriminated among the four types of margins. Moreover, the result also shows that, when retrieving round-shape and circumscribed margin masses, this retrieval system can achieve the highest precision among all mass lesion types.     

Fast image retrieval using color-spatial information

In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate the retrieval process. The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image. Two clusters from two images are similar if they are of the same color and overlap in the image space. The number of clusters that can be extracted from an image can be very large, and it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine an appropriate value for “optimal' performance. To facilitate efficient retrieval, we also propose a multi-tier indexing mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors, while the second layer discriminates clusters of different spatial locality. We conducted an experimental study on an image database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach, and the efficiency of the proposed indexing mechanism. Received August 1, 1997 / Accepted December 9, 1997     

Fast color-spatial feature based image retrieval methods

In this paper, three types of image features are proposed to describe the color and spatial distributions of an image. In these features, the K-means algorithm is adopted to classify all of the pixels in an image into several clusters according to their colors. By measuring the spatial distance among the pixels in a same cluster, the three types of color spatial distribution (CSD) features of the image is obtained. Based on the three types of CSD features, three image retrieval methods are also provided. To accelerate the image retrieval methods, a fast filter is also presented to eliminate most undesired images in advance. A genetic algorithm is also given to decide the most suitable parameters which are used in the proposed image retrieval methods. The proposed image retrieval methods are simple. Moreover, the experiments show that the proposed methods can provide impressive results as well.     

Fast and effective retrieval of medical tumor shapes

Investigates the problem of retrieving similar shapes from a large database; in particular, we focus on medical tumor shapes (finding tumors that are similar to a given pattern). We use a natural similarity function for shape matching, based on concepts from mathematical morphology, and we show how it can be lower-bounded by a set of shape features for safely pruning candidates, thus giving fast and correct output. These features can be organized in a spatial access method, leading to fast indexing for range queries and nearest-neighbor queries. In addition to the lower-bounding, our second contribution is the design of a fast algorithm for nearest-neighbor searching, achieving significant speedup while provably guaranteeing correctness. Our experiments demonstrate that roughly 90% of the candidates can be pruned using these techniques, resulting in up to 27 times better performance compared to sequential scanning     

基于DCT压缩的JPEG图像的快速检索

提出了一种基于离散余弦变换(DCT)压缩的JPEC图像的检索方法。该方法利用JPEG图像数据在DCT压缩域的特性,直接提取特征,而且只需要对JPEC进行部分熵解码。在加速了图像检索的过程的同时也保证了检索结果的精确性,并且具有一定的鲁棒性。     

Database retrieval for similar images using ICA and PCA bases

Similar-image retrieval systems are newly presented and examined. The systems use ICA bases (independent component analysis bases) or PCA bases (principal component analysis bases). These bases can contain source image's information, however, the indeterminacy of ordering and amplitude on the bases exists due to the PCA and ICA problem formulation per se. But, this paper successfully avoids this difficulty by using weighted inner products of similar bases. A set of opinion test is carried out on 18 systems according to the combination of {similarity measures (ICA, PCA, color histogram), color spaces (RGB, YIQ, HSV), filtering (with, without)}. The color histogram method is a traditional method. The opinion test shows that the presented method of {ICA, HSV, without filtering} is the best. Runners-up are {ICA, HSV or RGB or YIQ, with filtering}. The traditional method is judged to be much inferior. Thus, this paper's method is found quite effective to the similar-image retrieval from large databases.     

多任务分段紧凑特征的车辆检索方法

目的 随着公共安全领域中大规模图像监控及视频数据的增长以及智能交通的发展,车辆检索有着极其重要的应用价值。针对已有车辆检索中自动化和智能化水平低、难以获取精确的检索结果等问题,提出一种多任务分段紧凑特征的车辆检索方法,有效利用车辆基本信息的多样性和关联性实现实时检索。方法 首先,利用相关任务之间的联系提高检索精度和细化图像特征,因此构造了一种多任务深度卷积网络分段学习车辆不同属性的哈希码,将图像语义和图像表示相结合,并采用最小化图像编码使学习到的车辆的不同属性特征更具有鲁棒性;然后,选用特征金字塔网络提取车辆图像的实例特征并利用局部敏感哈希再排序方法对提取到的特征进行检索;最后,针对无法获取查询车辆目标图像的特殊情况,采用跨模态辅助检索方法进行检索。结果 提出的检索方法在3个公开数据集上均优于目前主流的检索方法,其中在CompCars数据集上检索精度达到0.966,在VehicleID数据集上检索精度提升至0.862。结论 本文提出的多任务分段紧凑特征的车辆检索方法既能得到最小化图像编码及图像实例特征,还可在无法获取目标检索图像信息时进行跨模态检索,通过实验对比验证了方法的有效性。     

基于L1范数的形状快速匹配算法

针对内距离形状上下文IDSC（inner-distance shape context）和轮廓点分布直方图CPDH（contours points distribution histogram）在形状相似性度量中直方图匹配耗时长,工程应用性不佳的问题,提出了一种用EMD-L1测量轮廓特征直方图的距离的方法。EMD-L1在原始EMD (earth mover’s distance)的基础上融合了L1范数,通过替换地面距离计算方法,减少了目标函数的变量,加快了直方图匹配的速度,能够快速实现形状匹配并保持较好的检索性能。对形状数据集进行仿真实验的结果证明,该方法能够有效地进行数据集的形状识别和检索,并且在MNIST数据集下的匹配速度优于其他算法。     

Fast retrieval of electronic messages that contain mistyped wordsor spelling errors

This paper presents an index structure for retrieving electronic messages that contain mistyped words or spelling errors. Given a query string (e.g., a search key), we want to find those messages that approximately contain the query, i.e., certain inserts, deletes and mismatches are allowed when matching the query with a word (or phrase) in the messages. Our approach is to store the messages sequentially in a database and hash their "fingerprints" into a number of "fingerprint files." When the query is given, its fingerprints are also hashed into the files and a histogram of votes is constructed on the messages. We derive a lower bound, based on which one can prune a large number of nonqualifying messages (i.e., those whose votes are below the lower bound) during searching. The paper presents some experimental results, which demonstrate the effectiveness of the index structure and the lower bound.     

基于八叉树的三维室内地图数据快速检索方法

针对室内三维地图中数据检索效率不高的问题，提出了一种基于八叉树的室内三维地图数据检索方法。首先，根据八叉树的场景分割方法对数据进行存储；然后，对数据进行编码以方便寻址；其次，为数据添加房间隔断约束条件对检索数据进行筛选；最后，对室内地图数据进行检索。与不具有约束条件的搜索方法相比，搜索代价平均降低了25个百分点，且搜索时间更加稳定。所提方法可以显著地提高室内三维地图数据的应用效率。     

基于加权灰关联的产品配置相似实例检索算法研究*

针对传统配置实例检索算法极少考虑实例属性间的关联性,结合欧几里得距离,将灰色关联理论应用到产品配置实例检索中,建立产品配置实例检索的灰色关联理论模型。利用层次分析法和熵技术来确定实例属性的权重值,避免了指标权重确定的主观性,增加检索结果的分辨性。最后通过一实例,证明该方法具有较好的分辨性。     

Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence

Chlorophyll fluorescence is related to photosynthesis and can serve as a remote sensing proxy for estimating photosynthetic energy conversion and carbon uptake. Recent advances in sensor technology allow remote measurements of the sun-induced chlorophyll fluorescence signal (Fs) at leaf and canopy scale. The commonly used Fraunhofer Line Depth (FLD) principle exploits spectrally narrow atmospheric oxygen absorption bands and relates Fs to the difference of the absorption feature depth of a fluorescensing and a non-fluorescensing surface. However, due to the nature of these narrow bands, Fs retrieval results depend not only on vegetation species type or environmental conditions, but also on instrument technology and processing algorithms. Thus, an evaluation of all influencing factors and their separate quantification is required to further improve Fs retrieval and to allow a reproducible interpretation of Fs signals.Here we present a modeling study that isolates and quantifies the impacts of sensor characteristics, such as spectral sampling interval (SSI), spectral resolution (SR), signal to noise ratio (SNR), and spectral shift (SS) on the accuracy of Fs measurements in the oxygen A band centered at 760 nm (O₂-A). Modeled high resolution radiance spectra associated with known Fs were spectrally resampled, taking into consideration the various sensor properties. Fs was retrieved using the three most common FLD retrieval methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD). The analysis investigates parameter ranges, which are representative for field and airborne instruments currently used in Fs research (e.g., ASD FieldSpec, OceanOptics HR, AirFLEX, AISA, APEX, CASI, and MERIS).Our results show that the most important parameter affecting the retrieval accuracy is SNR, SR accounts for ≤ 40% of the error, the SSI for ≤ 12%, and SS for ≤ 7% of the error. A trade-off study revealed that high SR can partly compensate for low SNR. There is a strong interrelation between all parameters and the impact of specific parameters can compensate or amplify the influence of others. Hence, the combination of all parameters must be considered by the evaluation of sensors and their potential for Fs retrieval. In general, the standard FLD method strongly overestimates Fs, while 3FLD and iFLD provide a more accurate estimation of Fs. We conclude that technical sensor specifications and the retrieval methods cause a significant variability in retrieved Fs signals. Results are intended to be one relevant component of the total uncertainty budget of Fs retrieval and have to be considered in the interpretation of retrieved Fs signals.     

Fast shape matching and retrieval based on approximate dynamic space warping

Dynamic space warping (DSW) has emerged as a very effective tool for matching shapes. However, a central computational difficulty associated with DSW arises when a boundary’s starting point (or rotation angle) is unknown. In this article, the HopDSW algorithm is proposed to speed up the starting point computation. Rather than performing an exhaustive search for the correct starting point as in classical approaches, the proposed algorithm operates in a coarse-to-fine manner. The coarse search is global and uses a hopping step to exclude points from the search. Then the search is refined in the neighborhood of the solution of the coarse search. A criterion that governs selecting the hopping step parameter is given, which reduces the number of starting point computations by an order. For shape representation, a triangle area signature (TAS) is computed from triangles formed by the boundary points. Experimental results on the MPEG-7 CE-1 database of 1400 shapes show that the proposed algorithm returns the solution to an exhaustive search with a high degree of accuracy and a considerable reduction in the number of computations.     

Fast K-means algorithm based on a level histogram for image retrieval

In image retrieval, the image feature is the main factor determining accuracy; the color feature is the most important feature and is most commonly used with a K-means algorithm. To create a fast K-means algorithm for this study, first a level histogram of statistics for the image database is made. The level histogram is used with the K-means algorithm for clustering data. A fast K-means algorithm not only shortens the length of time spent on training the image database cluster centers, but it also overcomes the cluster center re-training problem since large numbers of images are continuously added into the database. For the experiment, we use gray and color image database sets for performance comparisons and analyzes, respectively. The results show that the fast K-means algorithm is more effective, faster, and more convenient than the traditional K-means algorithm. Moreover, it overcomes the problem of spending excessive amounts of time on re-training caused by the continuous addition of images to the image database. Selection of initial cluster centers also affects the performance of cluster center training.     

Fast response and robust controller based on continuous eigenvalue configurations and time delay control

A soft variable structure point-to-point control scheme is proposed for a micro positioning system. The specific scheme is continuous eigenvalue configurations control combined with time delay control. By continuous tuning the state feedback control vector, the eigenvalues of the system will proceed continuously toward negative infinity, which will bring quick response. The simple tuning strategy is derived, which is a continuous function of displacement error. Furthermore, Time delay control is adopted to improve robustness to system uncertainties and disturbances. From the simulation and experimental results, the proposed control scheme provides good performances in settling time, positioning accuracy and disturbance rejection.     

Fast graph similarity search via hashing and its application on image retrieval

Similarity search in graph databases has been widely investigated. It is worthwhile to develop a fast algorithm to support similarity search in large-scale graph databases. In this paper, we investigate a k-NN (k-Nearest Neighbor) similarity search problem by locality sensitive hashing (LSH). We propose an innovative fast graph search algorithm named LSH-GSS, which first transforms complex graphs into vectorial representations based on prototypes in the database and later accelerates a query in Euclidean space by employing LSH. Because images can be represented as attributed graphs, we propose an approach to transform attributed graphs into n-dimensional vectors and apply LSH-GSS to execute further image retrieval. Experiments on three real graph datasets and two image datasets show that our methods are highly accurate and efficient.     

Fast retrieval of hidden data using enhanced hidden Markov model in video steganography

In the digital world, secure data communication has an important role in mass media and Internet technology. With the increase in modern malicious technologies, confidential data are exposed at a greater risk during data communication. For secured communication, recent technologies and the Internet have introduced steganography, a new way to hide data. Steganography is the growing practice of concealing data in multimedia files for secure data transfer. Nowadays, videos are more commonly chosen as cover media than other multimedia files because of the moving sequence of images and audio files. Despite its popularity, video steganography faces a significant challenge, which is a lack of a fast retrieval system of the hidden data. This study proposes a novel video steganography technique in which an enhanced hidden Markov model (EHMM) is employed to improve the speed of retrieving hidden data. EHMM mathematical formulations are used to enhance the speed of embedding and extracting secret data. The data embedding and retrieving operations were performed using the conditional states and the state transition dynamics between the video frames. The proposed EHMM is extensively evaluated using three benchmark functions, and experimental evaluations are conducted to test the speed of data retrieval using differently sized cover-videos. Results indicate that the proposed EHMM yields better results by reducing the data hiding time by 3–50%, improving the data retrieval rate by 22–77% with a minimum computational cost of 20–91%, and improving the security by 4–77% compared with state-of-the-art methods.