基于形状空间的鱼类识别

K. Nasreddine, A. Benzinou
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引用次数: 6

摘要

鱼类自动识别是一项新的研究工作,需要协助海洋科学家。在众多的判别特征中,鱼的轮廓对鱼的识别是非常有效的。在之前的工作中,我们提出了一种基于信号配准和形状测地线的模式识别(分类和检索)方法。在本文中,我们引入了姿态估计的初步步骤,以加快处理时间。然后,我们证明形状测地线也可以用于基于轮廓的鱼类识别。在SQUID数据库上进行的实验(SQUID数据库是评估鱼类形状识别的基准)表明:(1)计算时间平均减少了十倍;(2)与先前的方法相比,所提出的方案具有优异的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shape-based fish recognition via shape space
Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we introduce a preliminary step of pose estimation for accelerating the processing time. We then show that shape geodesics may also be used for outline-based fish recognition. Experiments conducted on the SQUID database which is used as a benchmark to evaluate fish shape recognition, show (1) a reduction in computation time of a factor of ten in average, and (2) the outperformance of the proposed scheme compared to previous methods.
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