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.
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.
15640953
Frequency layered color indexing for content-based image retrieval
Image patches of different spatial frequencies are likely to have different perceptual significance as well as reflect different physical properties. Incorporating such concept is helpful to the development of more effective image retrieval techniques. We introduce a method which separates an image into layers, each of which retains only pixels in areas with similar spatial frequency characteristics and uses simple low-level features to index the layers individually. The scheme associates indexing features with perceptual and physical significance thus implicitly incorporating high level knowledge into low level features. We present a computationally efficient implementation of the method, which enhances the power and at the same time retains the simplicity and elegance of basic color indexing. Experimental results are presented to demonstrate the effectiveness of the method.
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.
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
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>>
17880514
Concurrency Control for Mobile Systems with Data Broadcast
Although data broadcast has been shown to be an efficient method for disseminating data items in a mobile computing system with large number of clients, the issue on how to ensure the data consistency observed by mobile transactions, which are generated by mobile clients, has been largely ignored by researchers in the area. While data items are being broadcast, update transactions may install new values for the data items. If the executions of update and broadcast of data items are interleaved without any control, the mobile transactions may observe inconsistent data values. In this paper, we propose a serialization checking method (SCM) for concurrency control between read-only mobile transactions and update transactions. SCM is based on the framework of an earlier algorithm, Update First with Ordering (UFO), but improves on that algorithm by reducing re-broadcast overhead when the probability of data conflict between updates and data broadcast is high. Simulation experiments have been performed to investigate the performance characteristics of the proposed method.
12799586
Data broadcast for time-constrained read-only transactions in mobile computing systems
In this paper we propose broadcast algorithms, based on the policies proposed in previous studies, to disseminate data items to time-constrained read-only transactions. In the proposed algorithms, the number of data items requested by a transaction will be considered explicitly in selecting the data items for broadcast. The purpose of the algorithms is to reduce the number of transactions missing their deadlines, and to minimize their mean response time. A detailed simulation model of a mobile computing system has been developed and extensive simulation experiments have been performed to study the performance characteristics of the proposed broadcast algorithms, and the results show that our broadcast algorithms outperform previously proposed algorithms.
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.
7012036
The Reduced Ceiling Protocol for Concurrency Control in Real-time Databases with Mixed Transactions
This paper proposes a real-time concurrency control protocol called Reduced Ceiling Protocol (RCP) for real-time database systems (RTDBS) consisting of hard and soft real-time transactions. The schedulability of hard real-time transactions can be improved by bounding the blocking time from soft real-time transactions. Different concurrency control strategies are proposed to resolve data conflicts between different combinations of hard and soft real-time transactions, and the properties of the RCP schedules are shown. In the RCP, methodologies are proposed to reduce the number of aborts for soft real-time transactions due to data conflicts with hard real-time transactions. Simulation experiments have been performed to study the performance of the RCP as compared with the optimistic concurrency control with wait 50 (OCC wait-50) under different workloads of soft real-time transactions, various ratios of read/write operations, and deadline constraints. It has been found that the RCP can not only guarantee the performance of hard real-time transactions but also reduce the number of deadlines missed of the soft real-time transactions under all situations.