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Dynamic shape retrieval by hierarchical curve matching, snakes and data mining

机译:通过分层曲线匹配,蛇和数据挖掘的动态形状检索

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This paper presents a new approach to similar shape retrieval by coarse-to-fine curve matching and data mining techniques. The proposed method extends the concepts of conventional data warehouse and image database for effective image indexing. An image data warehouse schema is developed to integrate multiple shape features for hierarchical shape representation, dynamic similarity measures and fast query processing. A guided search scheme is introduced, that combines the methods of invariant moments, 2D polygonal arc matching and B-spline curve matching, to search for the best similar shape in a hierarchical fashion. The proposed method is applied to the tropical cyclone pattern recognition by utilizing the active contour model (snake) to extend the traditional Dvorak technique for tropical cyclone intensity analysis and forecasting from satellite imagery.
机译:本文通过粗曲线匹配和数据挖掘技术呈现了类似形状检索的新方法。该方法扩展了传统数据仓库和图像数据库的概念,以实现有效的图像索引。开发了一个图像数据仓库模式,以集成多种形状特征,以进行分层形状表示,动态相似度测量和快速查询处理。介绍了一个引导的搜索方案,它结合了不变矩,2D多边形弧匹配和B样条曲线匹配的方法,以以分层方式搜索最佳的相似性。通过利用活性轮廓模型(Snake)来延长热带气旋强度分析和从卫星图像预测的传统DVORAK技术来应用所述方法对热带气旋模式识别。

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