自适应图像检索及其在水下目标识别中的应用

J. Salazar, M. Azimi-Sadjadi
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引用次数: 1

摘要

本文研究了一种用于水下目标识别的自适应图像检索系统。利用从对比度和距离电光成像数据中提取的形状和纹理特征来表示每个类地雷或非类地雷样本图像。该检索系统是一个自适应的两层网络,其中第一层对专家用户的相关反馈具有结构适应性,而第二层仅在引入新类时才具有适应性。第二层的每个节点代表训练数据库中的一个样本图像。在大型光电图像数据库上的测试结果表明,该系统是一种自适应图像检索系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptable image retrieval with application to underwater target identification
This paper presents a study on an adaptable image retrieval system used for underwater target identification. Shape and textural features extracted from contrast and range electro-optical imagery data are used to represent each mine-like or non-mine-like sample image. The retrieval system is an adaptable two-layer network where the first layer is structurally adaptable in response to relevance feedback from expert users, while the second layer is adaptable only when a new class is introduced. Each node in the second layer represents one sample image in the training database. Test results on a large electro-optical imagery database are presented, which show the promise of the proposed system as an adaptable image retrieval system.
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