8132411
Human face recognition using a 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, Hausdroff 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 Hausdorff distance measure is proposed, which has a better noise immunity capability and better discriminant power. As the different facial regions have different relative importance for face recognition, the modified Hausdorff distance 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 82%, 93%, and 97% for the first, the first three, and the first five likely matched faces, respectively.
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.
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.
209064801
An accurate active shape model for facial feature extraction
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.
29622238
Optimistic concurrency control protocol for real-time databases
In recent years, the use of optimistic schemes for concurrency control in real-time database systems (RTDBS) has received more and more attention. Different real-time optimistic protocols have been proposed. They incorporate different priority conflict resolution methods into the validation phase of a transaction to give preferences for the commitment of higher priority transactions. However, some of these protocols suffer from the problem of heavy restart overheads. Restarting near-to-complete transactions greatly increases the system workload and the deadline missing probability of the transactions (Haritsa et al., 1992; Huang, 1991). In order to reduce the number of restarts, dynamic adjustment of the serialization order of the conflicting transactions has been suggested using timestamp intervals to record the transactions' serialization constraints (Lee and Son, 1993a, 1993b; Lee, 1994). However, these kinds of protocols have the problem of heavy implementation overheads as the timestamp intervals have to be checked and updated in case of any conflict even though the transactions are still in their read phases (Lee, 1994). In this paper, we propose a new real-time optimistic protocol which employs the notion of dynamic adjustment of serialization order by backward-adjusting the non-serious conflicting transactions before the committing transactions so that many restarts can be eliminated. In the protocol, the overhead to support dynamic adjustment of serialization order is small. All checking is performed at the validation test of a transaction so as to provide more freedom for the adjustments. No conflict and serialization constraints have to be recorded during the read phase of a transaction. Performance studies of the proposed protocol by varying different parameters indicate that it outperforms other protocols.
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.
909685
Enhanced multi-version data broadcast schemes for time-constrained mobile computing systems
We study the data dissemination problem in time-constrained mobile computing systems (TCMCS) in which maximizing data currency (minimizing staleness) and meeting transaction deadlines are of equal importance as providing consistent data items to transactions. We first investigate what are the performance problems of the multi-version data (MV) broadcast technique when it is used for TCMCS. Then, we propose various enhancements to resolve the problems. In order to further reduce the probability of missing deadlines, we introduce a prioritized on-demand broadcast scheme, which is integrated with the data broadcast mechanism for disseminating data items to time-constrained transactions. The performance characteristics of the proposed strategies have been studied through extensive simulation.
1690905
Broadcast of consistent data to read-only transactions from mobile clients
We study the inconsistency problem in data broadcast. While data items in a mobile computing system are being broadcast, update transactions may install new values for the data items. If the executions of update transactions and the broadcast of data items are interleaved without any control, it is possible that the mobile transactions, which are generated by mobile clients, may observe inconsistent data values. We propose a new algorithm, called Update-First with Order (UFO), for concurrency control among the mobile transactions and update transactions. The mobile transactions are assumed to be read-only. In the UFO algorithm, all the schedules among them are serializable. Two important properties of the UFO algorithm are that: (1) the mobile transactions do not need to set any lock before they read the data items from the "air"; and (2) its impact on the adopted broadcast algorithm, which has been shown to be an efficient method for data dissemination in mobile computing systems, is minimal.
206624081
Maintaining Temporal Consistency of Discrete Objects in Soft Real-Time Database Systems
A real-time database system contains base data items which record and model a physical, real-world environment. For better decision support, base data items are summarized and correlated to derive views. These base data and views are accessed by application transactions to generate the ultimate actions taken by the system. As the environment changes, updates are applied to base data, which subsequently trigger view recomputations. There are thus three types of activities: base data update, view recomputation, and transaction execution. In a real-time database system, two timing constraints need to be enforced. We require that transactions meet their deadlines (transaction timeliness) and read fresh data (data timeliness). In this paper, we define the concept of absolute and relative temporal consistency from the perspective of transactions for discrete data objects. We address the important issue of transaction scheduling among the three types of activities such that the two timing requirements can be met. We also discuss how a real-time database system should be designed to enforce different levels of temporal consistency.