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.
207326749
Optimal sampling of Gabor features for face recognition
The Gabor feature is effective for facial image representation, while linear discriminant analysis (LDA) can extract the most discriminant information from the Gabor feature for face recognition. In practice, the dimension of a Gabor feature vector is so high that the computation and memory requirements are prohibitively large. To reduce the dimension, one simple scheme is to extract the Gabor feature at sub-sampled positions, usually in a regular grid, in a face region. However, this scheme is not effective enough and degrades the recognition performance. In this paper, we propose a method to determine the optimal position for extracting the Gabor feature such that the number of feature points is as small as possible while the representation capability of the points is as high as possible. The subsampled positions of the feature points are determined by a mask generated from a set of training images by means of principal component analysis (PCA). With the feature vector of reduced dimension, a subspace LDA is applied for face recognition, i.e., PCA is first used to reduce the dimension of the Gabor feature vectors generated from the subsampled positions, and then a common LDA is applied. Experimental results show that the new sampling method is simple, and effective for both dimension reduction and image representation. The recognition rate based on our proposed scheme is also higher than that achieved using a regular sampling method in a face region.
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.
52318069
Pulling, Pushing, and Grouping for Image Segmentation
This paper presents a novel computational visual grouping method, termed pulling, pushing and grouping, or PPG for short. Visual grouping is formulated as a functional optimisation process. Our computational function has three terms, the first pulls similar visual cues together, the second pushes different visual cues apart, and the third groups spatially adjacent visual cues without regarding their visual properties. An efficient numerical algorithm based on the Hopfield neural model is developed for solving the optimisation process. Experimental results on various intensity, colour and texture images demonstrate the effectiveness of the new method.
61064863
Concurrency control in mobile distributed real-time database systems
Abstract With the rapid advances in mobile computing technology, there is an increasing demand for processing real-time transactions in a mobile environment. This paper studies concurrency control problem in mobile distributed real-time database systems (MDRTDBS). Based on the High Priority Two Phase Locking (HP-2PL) scheme, we propose a distributed real-time locking protocol, called Distributed High Priority Two Phase Locking (DHP-2PL), for MDRTDBS. In the protocol, the characteristics of a mobile computing system are considered in resolving lock conflicts. Two strategies are proposed to further improve the system performance and to reduce the impact of mobile network on the performance of the DHP-2PL: (1) A transaction shipping approach is proposed to process transactions in a mobile environment by exploring the well-defined behavior of real-time transactions. (2) We explore the application semantics of real-time database applications by adopting the notion of similarity in concurrency control to further reduce the number of transaction restarts due to priority inversion, which could be very costly in a mobile network. A detailed simulation model of a MDRTDBS has been developed, and a series of simulation experiments have been conducted to evaluate the performance of the proposed approaches and the effectiveness of using similarity for concurrency control in MDRTDBS.
35563029
An analysis of lock-based and optimistic concurrency control protocols in multiprocessor real-time databases
Abstract Previous studies, e.g., Haritsa et al. (Haritsa, J.R., Livny, M., Carey, M., 1990. Proceedings of Ninth ACM Symposium on Principles of Database systems) have shown that optimistic concurrency control (OCC) generally performs better than lock-based protocols in disk-based real-time database systems (RTDBS). In this paper we compare the two concurrency control protocols in both disk-based and memory-resident multiprocessor RTDBS. Based on simulation, we analyze the intrinsic behaviors of the two protocols. The result of our performance evaluation experiments show that different characteristics of the two environments indeed have great impact on the protocols' performance. We identify such system characteristics and expose the weaknesses of traditional OCC and lock-based protocols. To improve performance, a new protocol, called Two Phase Locking-Lock Write All (2PL-LW), is proposed. We show that 2PL-LW performs better than the traditional protocols in meeting transaction deadlines in both disk-based and memory-resident RTDBS.
8870380
Performance analysis of three related assignment problems
The relative placement of records in a database has a significant impact on the overall system performance. In this paper we study three related assignment problems. They are (1) the assignment of records to devices so as to minimize the expected completion time and to maximize the expected utilization of the devices, (2) the assignment of records to pages or blocks in secondary memory so as to minimize the number of blocks to be accessed, and (3) the analysis of the performance of a hashing scheme under the assumption that the record-to-bucket probability varies from one bucket to another. The solutions to these problems are obtained by studying an occupancy problem. In each case, an optimal solution is obtained.
16685984
A multi-version data model for executing real-time transactions in a mobile environment
With the significant advances in mobile computing technology, there is an increasing demand for various mobile applications to process transactions in a real-time fashion. When remote data access is considered in a mobile environment, data access delay becomes one of the most serious problems in meeting transaction deadlines. In this paper, we propose a multi-version data model and adopt the relative consistency as the correctness criterion for processing of real-time transactions in a mobile environment. The purpose is to reduce the impacts of unpredictable and unreliable mobile network on processing of the real-time transactions. Under the proposed model, the overheads for concurrency control can be significantly reduced, and the data availability is much enhanced even under network failures. A real-time transaction may access stale data, provided that they are relatively consistent with the data accessed by the transaction, and the staleness of the data is within the requirements. An image transaction model, which pre-fetches multiple data versions at fixed hosts, is proposed to reduce the data access delay and to simplify the management of the real-time transactions in a mobile environment. The image transaction model also helps in reducing the transaction-restart overheads and minimizing the impacts of the unpredictable performance of mobile network on transaction executions.
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.