Advanced Computational Frameworks for High-Accuracy Taxonomic Classification of Arowana Fish: Comparative Analysis of Asian and Australian Variants

The Asian Arowana (Scleropages formosus) is highly sought after in the ornamental fish market because of its rarity and cultural importance.Sadly, this demand has led to illegal trading, with Australian Arowanas (Scleropages leichardti and Scleropages jardinii) frequently being misrepresented as their Asian relatives, particularly in markets such as India.This paper presents a computational approach aimed at addressing these fraudulent activities by developing a reliable classification system to distinguish between Asian and Australian Arowanas.In this work we employ a machine learning framework that integrates image processing techniques with ResNet18, a deep convolutional neural network (CNN) in order to extract essential features from fish images.These features are then classified using a Support Vector Machine (SVM) hence resulting in a highly accurate model for taxonomic classification.The results demonstrate the effectiveness of this method in identifying species based on their morphological traits thus supporting both conservation efforts and consumer protection in the pet trade.This research offers a new, userfriendly tool for verifying the authenticity of Arowana species with potential implications for international trade regulation and wildlife conservation.50