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.
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.
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.
31880885
Channel-adaptive error protection for streaming stored MPEG-4 FGS over error-prone environments
In this paper, we investigate an adaptive channel error-protection scheme for streaming stored MPEG-4 fine granular scalability (FGS) bitstreams over error-prone environments. The human eye is sensitive to the variations in reconstructed image quality. Therefore, instead of using only the minimal average frame distortion as the optimization criterion, we propose a rate-distortion (R-D)-based bit-allocation method to determine the source coding rate and the channel coding rate under a given channel condition so as to minimize both the average image distortion and quality variation. Based on our proposed piecewise model of the MPEG-4 FGS enhancement layer, a balance between the average frame quality and quality variation will be obtained. Experimental results show that, compared with other existing methods, our proposed method can achieve less quality variation and comparable average frame distortion under various channel conditions.
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.
39491407
Mobile Distributed Real-Time Database Systems
17905998
Location update generation in cellular mobile computing systems
An important issue in the design of a mobile computing system is how to manage the real-time locations of mobile clients. In the existing commercial cellular mobile computing systems, a two-tier architecture is used (13). However, the two-tier architecture is not scalable and is not suitable to the new mobile computing applications. In the literatures (1, 12), a hierarchical database structure is proposed in which the location information of the 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 structure to facilitate the search of mobile clients. Although this architecture can distribute the update and searching workload amongst the location databases in the system, it has the problem of heavy location update overhead and long search delay. Thus, it is not suitable to the system which is supporting real-time queries. In this paper, we study how to generate location update in the distance-based update method. Two methods are proposed for calculating the optimal distance threshold with the objectives to minimize the total location management cost and the latency in searching the location of a mobile client.
27689226
Virtual deadline assignment in distributed real-time database systems
In recent years, the performance of distributed real-time database systems (DRTDBS) have been examined using different simulation models. In these models, the network issues are always being neglected. The networks are usually modeled as simple constant delay servers. However, it is found that the performance of the underlying network has significant impact on the overall performance of the DRTDBS. The results also showed that unpredictable behavior of the underlying network will give non-constant network transit time which in turn deter the overall system performance. To deal with this impact, different virtual deadline assignment schemes are proposed. The schemes assign a virtual deadline based on the current network condition to those transactions which require a comparatively better performance. Our results demonstrate that dynamically tuning the virtual deadlines of transactions depending on the condition of the network, yields a substantial improvement in the performance of that certain type of transactions without severely affecting the overall system performance.
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.
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.