Photo-identification has been proven to be a successful individual recognition tool in seahorse species (e.g., long-snout seahorse Hippocampus reidi (Ginsburg, 1933) and long-snouted seahorse Hippocampus guttulatus (Cuvier, 1829)). Its use was deemed valuable for the assessment of wild populations and to understand variations in abundance over time when capture-recapture methods are needed. In this study, a computer software with a pattern recognition algorithm (I3S® Contour 3.0) was used for individual identification of short-snouted seahorses Hippocampus hippocampus (Linnaeus 1758) in the laboratory. Using this methodology, differences in the shape of each individual’s coronet were tested as a unique and distinguishable characteristic. Two different contours were used as reference and tested to assess the effectiveness of this method in individual identification. A total of 94 captive-bred H. hippocampus, 45 adults (> 1 year old) and 49 young adults (4 months old), were tested. Positive matches were obtained in 55.1 % of the young adults and 84.4 % of the adults using contour 1; and in 77.6 % and 97.8 % for young adults and adults, respectively, using contour 2. All un-matched photos were later successfully matched by visual comparison, using additional traits (e.g., spot patterns) and gender. This methodology yielded very promising results and could be further used in wild individuals to allow population size estimates.

在海马物种中，照片识别已被证明是一种成功的个体识别工具（例如，长鼻海马海马reidi（金斯堡，1933年）和长鼻海马海马guttulatus（居维叶，1829年）。当需要捕获-再捕获方法时，其用途被认为对评估野生种群和了解丰度随时间的变化很有价值。在这项研究中，使用具有模式识别算法的计算机软件（I3S®Contour 3.0）来单独识别短食海马海马海马（Linnaeus 1758）在实验室。使用这种方法，将每个人的皇冠形状的差异作为一个独特且可区分的特征进行了测试。使用两个不同的轮廓作为参考，并进行了测试，以评估该方法在个人识别中的有效性。总共94圈养的ħ。海马测试了45位成年人（> 1岁）和49位年轻人（4个月大）。使用等高线1，在55.1％的年轻人和84.4％的成年人中获得了正面的匹配；而使用轮廓2的年轻人和成年人分别为77.6％和97.8％。后来，通过使用其他特征（例如斑点模式）和性别的视觉比较，成功匹配了所有不匹配的照片。这种方法产生了非常有希望的结果，可以在野外个体中进一步使用以估计种群数量。