18536131
An efficient color compensation scheme for skin color segmentation
Skin color is a useful means for human face detection. In this paper, we propose an efficient color compensation method for skin color segmentation under varying lighting conditions. One of the major problems of using skin color is that a face region may not be detected under poor or uneven lighting conditions. Our approach considers the distribution of the color components of skin pixels and the color response of capturing machines under different illuminations. Experimental results show that this algorithm can improve the performance of face segmentation under poor or strong lighting conditions.
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.
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.
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.
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.
6241607
Location management in cellular mobile computing systems with dynamic hierarchical location databases
An important issue in the design of a mobile computing system is how to manage the location information of mobile clients. In the existing commercial cellular mobile computing systems, a two-tier architecture is adopted. However, the two-tier architecture is not scalable. In the literatures, a hierarchical database structure is proposed in which the location information of mobile clients within a cell is managed by the location database responsible for the cell. The location databases of different cells are organized into a tree-like structure to facilitate the search of mobile clients. Although this architecture can distribute the updates and the searching workload amongst the location databases in the system, location update overheads can be very expensive when the mobility of clients is high. In this paper, we study the issues on how to generate location updates under the distance-based method for systems using hierarchical location databases. A cost-based method is proposed for calculating the optimal distance threshold with the objective to minimize the total location management cost. Furthermore, under the existing hierarchical location database scheme, the tree structure of the location databases is static. It cannot adapt to the changes in mobility patterns of mobile clients. This will affect the total location management cost in the system. In the second part of the paper, we present a reorganization strategy to restructure the hierarchical tree of location databases according to the mobility patterns of the clients with the objective to minimize the location management cost. Extensive simulation experiments have been performed to investigate the reorganization strategy when our location update generation method is applied.
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.
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.
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.