# Identification of Shark Species Based on Their Dry Dorsal Fins through Image Processing
## 1 Introduction  
The increased human exploitation and habitat deterioration over the last half-century has decreased shark populations worldwide [1; 2]. Consequently, more than one-third of chondrichthyan species (sharks, rays, and chimeras, hereafter referred to as'sharks') are threatened with extinction due to a myriad of human-caused threats; however, observed population declines are driven primarily by overexploitation in largely unregulated and unmonitored target and dycatch fisheries worldwide [3]. A global catch assessment estimated that approximately 100 million sharks are caught annually worldwide, including illegal, unreported, and unregulated catch [4]. The reassessment of 1199 species by the International Union for Conservation of Nature (IUCN) Red List reveals that almost 400 chondrichthyan species are jeopardized with extinction [5]. International efforts to improve the management and conservation of sharks have focused on the use of multilateral environmental agreements, such as the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), to ensure that products derived from shark and ray species are traded legally and sustainably [6]. At present, CITES has listed 46 shark and ray species in the Appendices, and the participating184 countries worldwide should monitor and control trading of shark products to ensure sustainability, legality, and traceability from international trade operations [7]. Economic globalization and exploitation of sharks have strengthened the demand and supply of domestic and international markets for sharks and ray products (mainly meat and fins) [8]. Shark meat markets have remained stable over the last decade, with Brazil, Spain, Uruguay, and Italy accounting for 57% of the average global shark meat imports [9; 10; 11]. In contrast, Hong Kong and mainland China are major worldwide trade and consumption centers for seafood, where shark fins are considered a prized cultural treasure and luxury food items, such as sharkfin soup--which is served on formal and special occasions [12]. Unfortunately, international trade data for sharks and their derivative products are rarely collected at the species level, hampering the monitoring of shark species or their derivative parts, such as fins and meat [8]. This represents a major challenge for the implementation of effective monitoring, enforcement, and requirements of countries--referred to as parties--in meeting their obligations under CITES [13]. To achieve compliance with domestic and international regulations for the shark fin trade, there are several accessible identification tools to aid in the implementation of CITES trade controls for listed species, both domestically and at various points along the supply chain (i.e., software iSharkFin version number 1.4, fin guides, and genetic approaches). First, the bioinformatics tool, iSharkFin, developed by FAO and the University of Vigo, was designed to identify 39 species from wet shark fins [14; 15]; however, some limitations need to be considered when using this software, including the misidentification of CITES-listed species, particularly when dry fins are analyzed because of the discordance between iSharkFin results, visual diagnostic characteristics, and genetic identification. Currently, this is the only software that is working. Second, several visual shark fin identification (ID) guides can provide users with a fast and cheap tool for the identification of unprocessed fins from CITES species based on the morphological characteristics of certain fin types, such as the shape and coloration patterns [16; 17; 18; 19; 20]; however, the effectiveness of fin ID guides is highly dependent on the training and expertise of users in identifying fins from morphologically distinct species, such as _Sphyrna lewini_ and _S. zygaen_[20].