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.
33676247
Locating and extracting the eye in human face images
Facial feature extraction is an important step in automated visual interpretation and human face recognition. Among the facial features, the eye plays the most important part in the recognition process. The deformable template can be used in extracting the eye boundaries. However, the weaknesses of the deformable template are that the processing time is lengthy and that its success relies on the initial position of the template. In this paper, the head boundary is first located in a head-and-shoulders image. The approximate positions of the eyes are estimated by means of average anthropometric measures. Corners, the salient features of the eyes, are detected and used to set the initial parameters of the eye templates. The corner detection scheme introduced in this paper can provide accurate information about the corners. Based on the corner positions, we can accurately locate the templates in relation to the eye images and greatly reduce the processing time for the templates. The performance of the deformable template is assessed with and without using the information on corner positions. Experiments show that a saving in execution time of about 40% on average and a better eye boundary representation can be achieved by using the corner information.
14714935
An efficient low bit-rate video-coding algorithm focusing on moving regions
Block-based motion estimation and compensation are the most popular techniques for video coding. However, as the shape and the structure of an object in a picture are arbitrary, the performance of such conventional block-based methods may not be satisfactory. In this paper, a very low bit-rate video coding algorithm that focuses on moving regions is proposed. The aim is to improve the coding performance, which gives better subjective and objective quality than that of the conventional coding methods at the same bit rate. Eight patterns are pre-defined to approximate the moving regions in a macroblock. The patterns are then used for motion estimation and compensation to reduce the prediction errors. Furthermore, in order to increase the compression performance, the residual errors of a macroblock are rearranged into a block with no significant increase of high-order DCT coefficients. As a result, both the prediction efficiency and the compression efficiency are improved.
12206604
An adaptive active contour model for highly irregular boundaries
Abstract Snake is an active contour model for representing image contours. In this paper, we propose an efficient active contour model which can represent highly irregular boundaries. The algorithm includes an adaptive force along the contour, and adjusts the number of points for the snake according to the desired boundary. A better stopping criterion based on the area of a closed contour is devised. Furthermore, in this method, a contour can break automatically to represent the contours of multiple objects. Experiments show that this method can extract object's boundaries accurately and efficiently.
721061
A fast fractal image coding based on kick-out and zero contrast conditions
A fast algorithm for fractal image coding based on a single kick-out condition and the zero contrast prediction is proposed in this paper. The single kick-out condition can avoid a large number of range-domain block matches when finding the best matched domain block. An efficient method for zero contrast prediction is also proposed, which can determine whether the contrast factor for a domain block is zero or not, and compute the corresponding difference between the range block and the transformed domain block efficiently and exactly. The proposed algorithm can achieve the same reconstructed image quality as the exhaustive search, and can greatly reduce the required computation or runtime. In addition, this algorithm does not need any pre-processing step or additional memory for its implementation, and can combine with other fast fractal algorithms to further improve the speed. Experimental results show that the runtime is reduced by about 50% of that of the exhaustive search method. When combined with the DCT Inner Product algorithm, the required runtime for the algorithm can be further reduced by about 50%. The proposed algorithm was also compared to two other fast fractal algorithms. Experimental results also show that our algorithm achieves a better efficiency and requires a much smaller amount of memory for implementation.
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.
2822009
An Approach to Probabilistic Retrieval
The objective is to relate the effectiveness of retrieval, the fuzzy set concept and the processing of Boolean query. The use of a probabilistic retrieval scheme is motivated. It is found that there is a correspondence between probabilistic retrieval schmes and fuzzy sets. A fuzzy set corresponding to a potentially optimal probabilistic retrieval scheme is obtained. Then the retrieval scheme for the fuzzy set is constructed.
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.
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.
18060824
Performance evaluation of a new distributed deadlock detection algorithm
In this paper, a new probe-based distributed deadlock detection algorithm is proposed. It is an enhanced version of the algorithm originally proposed by Chandy's et al. [5,6]. The new algorithm has proven to be error free and suffers very little performance degradation from the additional deadlock detection overhead. The algorithm has been compared with the modified probe-based and timeout methods. It is found that under high data contention, it has the best performance. Results also indicate that the rate of probe initiation is significantly reduced in the new algorithm.
17015154
Priority and deadline assignment to triggered transactions in distributed real-time active databases
Abstract A distributed real-time active database system (DRTADBS) reacts to the critical events that 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. Two new approaches, the data state dependent (DSD) and the transaction-data deadline (TDD), are proposed to assign criticality and deadlines 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. The TDD approach can improve the system performance under both deferred and immediate coupling mode.