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.
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.
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
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.
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.
32813168
Resolving conflicts with committing transactions in distributed real-time databases
In a distributed real-time database system, if data conflicts occur between executing and committing transactions, the performance can be severely affected. In this paper, we propose an approach, called deadline driven conflict resolution (DDCR), which integrates concurrency control and commitment management in resolving data conflicts between executing and committing transactions, while at the same time maintaining the schedules to be serializable. With DDCR, many of the data conflicts can be alleviated, and concurrent execution of transactions is allowed to access data items being held by committing transactions. The impact of temporary failures occurred during the commitment of a transaction on other transactions is reduced by reversing the dependencies between the transactions. Simulation experiments have been performed and the results show that DDCR can significantly improve the system performance especially when the duration for the voting phase is long.
5051365
Promising Approach to Distributed Query Processing
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.
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.