27390874
Color Sectors and Edge Features for Content-Based Image Retrieval
We provide a new image retrieval model which integrates the spatial distributing information of colors and the shape features. The color features are represented by an amelioration of HSV color model: color sector. To describe the relative position and orientation of objects within the image, hue edges in the image, computed using Canny approach, are processed by Hough transform to generate the spatial histogram which is used as shape representation. To address matching of image, we define two global distance measures based on the accumulative distance and vector-based distance to compare the similarity of two images. Experimental results indicate that our approach provides higher retrieval rate than that of single feature (color), is a better tradeoff between high efficiency and reasonable precision.
6876954
A New Backoff Algorithm for IEEE 802.11 Distributed Coordination Function
DCF (Distributed Coordination Function) of IEEE802.11 MAC protocols uses binary exponential increasing mechanism, called BEB (Binary Exponential Backoff) algorithm. Due to the lack of a mechanism evaluating the channel condition, it can not tune the value of contention windows adaptively, according to the actual network traffic. By introducing the network allocation vector count in routing protocol to approximate the intensity of surrounding traffic of nodes, the algorithm has been improved, so that the contention windows of backoff mechanism are adjusted reasonably according to the traffic of WLAN. Simulation experiments are done and the results prove that the improved algorithm provides a better channel utilization and reduces the average transmission delay.
42929157
Real-Time Digital Signal Processing of Phased Array Radars
With the advance of hardware and software technology, modern phased array radars are now built with commercial-off-the-shelf (COTS) components, and it opens up a new era in real-time resource scheduling of digital signal processing. This paper targets the essential issues in building a component-oriented signal processor (SP), which is one of the two major modules in modern phased array radars. We propose a simple but effective task allocation policy and a real-time scheduling algorithm to address the design objectives of SPs. We are able to bound the number of processing units needed for a component-oriented SP in the design time, while everything was done empirically in the past. A series of experiments was done to demonstrate the strength of our methodology.
15209820
Real-time digital signal processing of component-oriented phased array radars
With the advance of hardware and software technology, modern phased array radars are now built with commercial off-the-shelf (COTS) components, and it opens up a new era in real-time resource scheduling of digital signal processing. This paper targets the essential issues in building a component-oriented signal processor (SP), which is one of the two major modules in modern phased array radars. We propose a simple but effective task allocation policy and a real-time scheduling algorithm to address the design objectives of SPs. We are able to bound the number of processing units needed for a component-oriented SP in the design time, while everything was done empirically in the past. A series of experiments were done to demonstrate the strength of our methodology.
18355867
Multi-granularity Visualization of Trajectory Clusters Using Sub-trajectory Clustering
With the surging of the requirements of location-based services, mining various interesting patterns from the spatial data becomes more and more important. In this paper, we propose an approach for visualizing the trajectory clustering results based on sub-trajectory clusters discovered from large-scale trajectory data. At first, we segment each trajectory into a set of sub-trajectories by detecting its corner points. And then, we choose Fréchet distance to compute the similarity between sub-trajectories, and use a density-based clustering method to cluster sub-trajectories and get an augmented order of the sub-trajectories. The visualization method can support multi-granularity views of the generated sub-trajectory clusters. Experiments have demonstrated the applicability and benefits of the proposed approach.
782406
Data Compression
9272685
Genetic algorithm for affine point pattern matching
Point pattern matching (PPM) is an important topic in the fields of computer vision and pattern recognition. According to if there exists a one to one mapping between the two point sets to be matched, PPM can be divided into the case of complete matching and the case of incomplete matching. According to if utilizing information other than 2-D image coordinates, PPM can be divided into labelled point-matching case and unlabelled point-matching case. Using partial Hausdorff distance, this paper presents a genetic algorithm (GA) based method to solve the incomplete unlabelled matching problem under general affine transformation. Since it successfully reduces the solution space of GA by constructing 'feature ellipses' of point sets, the method can achieve high computing efficiency and good matching results. Theoretical analysis and simulation results show that the new algorithm is very effective.