In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact t...In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach.展开更多
针对尾矿坝在线监测重建设、轻利用的现状,基于尾矿坝位移在线监测时间序列,通过多步逆向云变换算法(Multi-step Backward Cloud Transformation Algorithm Based on Sampling with Replacement,MBCT-SR)改进云模型,根据“3E_(n)原则”...针对尾矿坝在线监测重建设、轻利用的现状,基于尾矿坝位移在线监测时间序列,通过多步逆向云变换算法(Multi-step Backward Cloud Transformation Algorithm Based on Sampling with Replacement,MBCT-SR)改进云模型,根据“3E_(n)原则”和内外包络曲线确定在线监测位移的正常运行值,从而建立尾矿坝位移分级预警阈值模型,并利用某尾矿坝全球导航卫星(Global Navigation Satellite System,GNSS)技术表面位移在线监测数据进行实例验证。结果表明:该尾矿坝水平方向位移的黄、橙、红预警阈值分别为8.41 mm/d、12.94 mm/d、19.41 mm/d,呈现出坝体中间预警阈值最大、并由中间向两侧减小的空间变化规律;尾矿坝垂直方向位移的黄、橙、红预警阈值分别为16.56 mm/d、25.48 mm/d、38.22 mm/d,且随着子坝的堆积,预警阈值逐渐增大。展开更多
文摘In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach.
