In this paper, a hierarchical grid-based indexing method for content-based image retrieval (CBIR) is proposed to improve the retrieval performance. To develop a general retrieval scheme which is less dependent on domain-specific knowledge, the discrete cosine transform (DCT) is employed as a feature extraction method. In establishing database, quantization technique is applied to quantize the DCT coefficients of each database image, such that the feature space is partitioned into a finite number of grids, each of which corresponds to a grid code (GC). On querying an image, a reduced set of candidate images which have the same GC as that of the query image is obtained at varying levels of grid granularity. In the fine matching stage, only the remaining candidates need to be computed for the detailed similarity comparison. The experimental results show that the proposed method leads to a fast retrieval with good accuracy.
Abstract-Network devices including firewall, QoS, Anti-Virus wall, IDS and so on were developed to help administrators monitor internet usage behaviors in response to network applications. However, it requires administrators to log on different network devices for acquiring associated usage logs for further respective analysis whenever abnormal network usage behavior occurred. It is both difficult and time consuming for administrators to manage usage logs from all the devices within a network. Therefore, how to provide administrators integrated information through one single platform for more effective management and efficient data inquiry is the aim of this research. This study proposed the measure that the usage logs from network devices can be stored in the data warehouse where the necessary information within a specific timeframe was acquired by business intelligence system for further comparison and integration. It can save the time for log inquiries and assist efficient network users behavior analysis.
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