A String Matching Computer-Assisted System for Dolphin Photoidentification

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.

Iterative 3-D Pose Correction and Content-Based Image Retrieval for Dorsal Fin Recognition

“…Methods for the computer assisted identification of individual marine mammals have been proposed for a variety of different species including gray seals [5], sperm whales [15], [7], dolphins [4], [10], [1], humpback whales [12], [14] and right whales [2], [6]. Identifying dolphins by the comparison of dorsal fins is similar to whale identification based upon fluke characteristics such as highly visible pigmentation patterns.…”

Learning Features for Identifying Dolphins

“…For curvature feature extraction, we propose a method that differs from those proposed by Araabi (2000), Hillman (1998), and Gopi (2005), cited previously. Our method generates two third degree polynomials, one for each side of the fin.…”

An automated chimpanzee identification system using face detection and recognition

“…Ardovini et al [26] for instance proposed a system for semiautomatic recognition of elephants from photos based on shape comparison of the nicks characterizing the elephant's ears. A similar approach was presented by Araabi et al [27], who proposed a string matching method as part of a computer-assisted system for dolphin identification from images of their dorsal fin. Also Burghardt et al [28,29] presented a fully automatic system for penguin identification.…”