18244295
An efficient illumination normalization method for face recognition
In this paper, an efficient representation method insensitive to varying illumination is proposed for human face recognition. Theoretical analysis based on the human face model and the illumination model shows that the effects of varying lighting on a human face image can be modeled by a sequence of multiplicative and additive noises. Instead of computing these noises, which is very difficult for real applications, we aim to reduce or even remove their effect. In our method, a local normalization technique is applied to an image, which can effectively and efficiently eliminate the effect of uneven illuminations while keeping the local statistical properties of the processed image the same as in the corresponding image under normal lighting condition. After processing, the image under varying illumination will have similar pixel values to the corresponding image that is under normal lighting condition. Then, the processed images are used for face recognition. The proposed algorithm has been evaluated based on the Yale database, the AR database, the PIE database, the YaleB database and the combined database by using different face recognition methods such as PCA, ICA and Gabor wavelets. Consistent and promising results were obtained, which show that our method can effectively eliminate the effect of uneven illumination and greatly improve the recognition results.
5893059
Hybrid Chinese/English text detection in images and video frames
We propose a multiscale texture-based method using local energy analysis for hybrid Chinese/English text detection in images and video frames. Local energy analysis has been shown to work well in text detection, where remarkable local energy variations of pixels correspond to text region or boundary of other objects and lower local energy variations of pixels correspond to background or the interior of non-text objects. Local energy variation is calculated in a local region based on the wavelet transform coefficients of images. Hybrid Chinese/English text in images and video frames can be detected whether it is aligned horizontally or vertically. The font size of text to be detected may vary in a wide range of values. The proposed method has been tested on 321 frame images obtained from local TV programs and a tested dataset with low missed rate and false alarm rate.
26133489
Robust Hausdorff distance for shape matching
The Hausdorff distance can be used to measure the similarity of two point sets. In matching the two point sets, one of them is translated, rotated and scaled in order to obtain an optimal matching, which is a computationally intensive process. In this paper, a robust line-feature-based approach for model-based recognition is presented, which can achieve good matching, even in a noisy environment or with the existence of occlusion. We propose three different ways for forming the line segments for a point set. Two of the methods are based on a fixed reference point, which are the centroid and the center of the minimal disk of the point set. The third method is based on the longest possible line segments formed within the point set. The line features extracted based on the respective line segments are insensitive to noise and can be used to determine the rotation and scale of the image point set accurately and reliably, and more importantly, 2D-2D matching algorithm can be adopted. The first 2D-matching is to compute the relative scale and orientation between the two point sets. Having rotated and scaled the image point set, the M-Estimation Hausdorff distance is applied for the second 2D-matching to measure the relative translation between the query point set and the model point set. This 2D-2D matching can greatly reduce the required memory and computation when compared to a 4D-matching. Both the performance and the sensitivity to noise of our algorithms are evaluated using simulated data. Experiments show that our 2D-2D algorithms can yield a high level of performance when determining the scale, the orientation and the similarity of two point sets.
209064801
An accurate active shape model for facial feature extraction
28287084
Human face recognition based on spatially weighted Hausdorff distance
The edge map of a facial image contains abundant information about its shape and structure, which is useful for face recognition. To compare edge images, Hausdorff distance is an efficient measure that can determine the degree of their resemblance, and does not require a knowledge of correspondence among those points in the two edge maps. In this paper, a new modified Hansdorff distance measure is proposed, which has a better discriminant power. As different facial regions have different degrees of significance for face recognition, a new modified Hausdorff distance is proposed which is weighted according to a weighted function derived from the spatial information of the human face; hence crucial regions are emphasized for face identification. Experimental results show that the distance measure can achieve recognition rates of 80%, 87%, and 91% for the first, the first five, and the first seven likely matched faces, respectively.
39178482
Illumination invariant face recognition
The appearance of a face will vary drastically when the illumination changes. Variations in lighting conditions make face recognition an even more challenging and difficult task. In this paper, we propose a novel approach to handle the illumination problem. Our method can restore a face image captured under arbitrary lighting conditions to one with frontal illumination by using a ratio-image between the face image and a reference face image, both of which are blurred by a Gaussian filter. An iterative algorithm is then used to update the reference image, which is reconstructed from the restored image by means of principal component analysis (PCA), in order to obtain a visually better restored image. Image processing techniques are also used to improve the quality of the restored image. To evaluate the performance of our algorithm, restored images with frontal illumination are used for face recognition by means of PCA. Experimental results demonstrate that face recognition using our method can achieve a higher recognition rate based on the Yale B database and the Yale database. Our algorithm has several advantages over other previous algorithms: (1) it does not need to estimate the face surface normals and the light source directions, (2) it does not need many images captured under different lighting conditions for each person, nor a set of bootstrap images that includes many images with different illuminations, and (3) it does not need to detect accurate positions of some facial feature points or to warp the image for alignment, etc.
28390407
Scheduling of Triggered Transactions in Distributed Real-Time Active Databases
A Distributed Real-time Active Database System reacts to the critical events occurred in the external environment by triggering of transactions. In this paper, the priority and deadline assignment to triggered transactions under two coupling modes, the deferred and immediate, in a DRTADBS is discussed. A new approach, the data state dependent (DSD) is proposed to assign criticality to the triggered transactions, respectively. In the DSD approach, the criticality of a triggered transaction is defined according to the state of the temporal data object which is responsible for its triggering. The objective of the DSD approach is to increase the number of commit achieved by the triggered transactions especially the more critical ones. The performance of these two approaches under the two coupling modes has been investigated. The results show that the DSD approach is more effective under the immediate coupling mode than under the deferred coupling mode due to the late creation of the triggered transactions under the deferred coupling mode.
1484243
RTMonitor: Real-Time Data Monitoring Using Mobile Agent Technologies
RTMonitor is a real-time data management system for traffic navigation applications. In our system, mobile vehicles initiate time-constrained navigation requests and RTMonitor calculates and communicates the best paths for the clients based on the road network and real-time traffic data. The correctness of the suggested routes highly depends on how well the system can maintain temporal consistency of the traffic data. To minimize the overheads of maintaining the real-time data, RTMonitor adopts a cooperative and distributed approach using mobile agents which can greatly reduce the amount of communications and improves the scalability of the system. To minimize the space and message overheads, we have designed a two-level traffic graph scheme to organize the real-time traffic data to support navigation requests. In the framework, the agents use an Adaptive PUSH OR PULL (APoP) scheme to maintain the temporal consistency of the traffic data. Our experiments using synthetic traffic data show that RTMonitor can provide efficient support to serve navigation requests in a timely fashion. Although several agents may be needed to serve a request, the size of each agent is very small (only a few kilobytes) and the resulting communication and processing overheads for data monitoring can be maintained within a reasonable level.
16770370
Impact of priority assignment on optimistic concurrency control in distributed real-time databases
In the studies of real-time concurrency control protocols (RT-CCPs), it is always assumed that earliest deadline first (EDF) is employed as the CPU scheduling algorithm. However, using purely (ultimate) deadline for priority assignment may not be suitable for distributed real-time database systems (DRTDBS) in which there exist different kinds of transactions, such as global and local transactions. In order to improve the performance, different priority assignment heuristics have to be used. In this paper, we have investigated the performance of different priority assignment heuristics for sub-transactions in DRTDBS with optimistic concurrency control (OCC) protocol. If is found that the heuristics, which are suitable for distributed real-time systems, are not suitable for DRTDBS. We find that our proposed heuristic, which considers both deadline constraint and data contention, can give the best performance.
42222241
Efficient technique for performance analysis of locking protocols
The validity of many analytic studies of the performance of database systems are often hampered by the many approximations made. This is especially true of the way the block queue delays and deadlocks have been handled. An efficient approach to the derivation of the blocking delays of transactions under the static and dynamic two phase locking protocols is given. The problem of deadlocks which has either been neglected or assumed to be of cycle-length two (involving two transactions only) has also been tackled with some degree of success. The analysis is based on simple combinatorial arguments and probability theory. MVA techniques are then applied to the two models. Several conclusions can be drawn regarding the behaviour of the database systems. The analytic results show remarkable good agreement with simulation results.<<ETX>>
62523912
Concurrency control strategies for ordered data broadcast in mobile computing systems
Although data broadcast has been shown to be an efficient method for disseminating data items in mobile computing systems, the issue on how to ensure consistency and currency of data items provided to mobile transactions (MT), which are generated by mobile clients, has not been examined adequately. While data items are being broadcast, update transactions may install new values for them. If the executions of update transactions and the broadcast of data items are interleaved without any control, mobile transactions may observe inconsistent data values. The problem will be more complex if the mobile clients maintain some cached data items for their mobile transactions. In this paper, we propose a concurrency control method, called ordered update first with order (OUFO), for the mobile computing systems where a mobile transaction consists of a sequence of read operations and each MT is associated with a time constraint on its completion time. Besides ensuring data consistency and maximizing currency of data to mobile transactions, OUFO also aims at reducing data access delay of mobile transactions using client caches. A hybrid re-broadcast/invalidation report (IR) mechanism is designed in OUFO for checking the validity of cached data items so as to improve cache consistency and minimize the overhead of transaction restarts due to data conflicts. This is highly important to the performance of the mobile computing systems where the mobile transactions are associated with a deadline constraint on their completion times. Extensive simulation experiments have been performed to compare the performance of OUFO with two other efficient schemes, the multi-version broadcast method and the periodic IR method. The performance results show that OUFO offers better performance in most aspects, even when network disconnection is common.