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一种用于海豚照片识别的字符串匹配计算机辅助系统。

A string matching computer-assisted system for dolphin photoidentification.

作者信息

Araabi B N, Kehtarnavaz N, McKinney T, Hillman G, Würsig B

机构信息

Electrical Engineering Department, Texas A & M University, College Station 77843-3128, USA.

出版信息

Ann Biomed Eng. 2000;28(10):1269-79. doi: 10.1114/1.1317532.

Abstract

This paper presents a syntactic/semantic string representation scheme as well as a string matching method as part of a computer-assisted system to identify dolphins from photographs of their dorsal fins. A low-level string representation is constructed from the curvature function of a dolphin's fin trailing edge, consisting of positive and negative curvature primitives. A high-level string representation is then built over the low-level string via merging appropriate groupings of primitives in order to have a less sensitive representation to curvature fluctuations or noise. A family of syntactic/semantic distance measures between two strings is introduced. A composite distance measure is then defined and used as a dissimilarity measure for database search, highlighting both the syntax (structure or sequence) and semantic (attribute or feature) differences. The syntax consists of an ordered sequence of significant protrusions and intrusions on the edge, while the semantics consist of seven attributes extracted from the edge and its curvature function. The matching results are reported for a database of 624 images corresponding to 164 individual dolphins. The identification results indicate that the developed string matching method performs better than the previous matching methods including dorsal ratio, curvature, and curve matching. The developed computer-assisted system can help marine mammalogists in their identification of dolphins, since it allows them to examine only a handful of candidate images instead of the currently used manual searching of the entire database.

摘要

本文提出了一种句法/语义字符串表示方案以及一种字符串匹配方法,作为计算机辅助系统的一部分,用于从海豚背鳍照片中识别海豚。基于海豚鳍后缘的曲率函数构建低级字符串表示,其由正曲率和负曲率基元组成。然后通过合并适当的基元分组在低级字符串之上构建高级字符串表示,以便对曲率波动或噪声具有较低的敏感性。引入了两个字符串之间的一系列句法/语义距离度量。然后定义一个复合距离度量并将其用作数据库搜索的不相似度度量,突出句法(结构或序列)和语义(属性或特征)差异。句法由边缘上显著的凸起和凹陷的有序序列组成,而语义由从边缘及其曲率函数中提取的七个属性组成。报告了针对包含164只个体海豚的624幅图像数据库的匹配结果。识别结果表明,所开发的字符串匹配方法比包括背鳍比例、曲率和曲线匹配在内的先前匹配方法表现更好。所开发的计算机辅助系统可以帮助海洋哺乳动物学家识别海豚,因为它使他们只需检查少数候选图像,而不必像目前那样手动搜索整个数据库。

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