Superimposed Image Description and Retrieval for Fish Species Identification
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Προβολή/ Άνοιγμα
Ημερομηνία
2009Συγγραφέας
Murthy, Uma
Fox, Edward A.
Chen, Yinlin
Hallerman, Eric
Da Silva Torres, Ricardo
Ramos, Evandro J.
Falcao, Tiago R.C.
Metadata
Εμφάνιση πλήρους εγγραφήςΕπιτομή
Fish species identification is critical to the study of fish ecology
and management of fisheries. Traditionally, dichotomous keys are
used for fish identification. The keys consist of questions about the observed
specimen. Answers to these questions lead to more questions till
the reader identifies the specimen. However, such keys are incapable of
adapting or changing to meet different fish identification approaches, and
often do not focus upon distinguishing characteristics favored by many
field ecologists and more user-friendly field guides. This makes learning
to identify fish difficult for Ichthyology students. Students usually supplement
the use of the key with other methods such as making personal
notes, drawings, annotated fish images, and more recently, fish information
websites, such as Fishbase. Although these approaches provide useful
additional content, it is dispersed across heterogeneous sources and can
be tedious to access. Also, most of the existing electronic tools have limited
support to manage user created content, especially that related to
parts of images such as markings on drawings and images and associated
notes. We present SuperIDR, a superimposed image description and retrieval
tool, developed to address some of these issues. It allows users to
associate parts of images with text annotations. Later, they can retrieve
images, parts of images, annotations, and image descriptions through
text- and content-based image retrieval. We evaluated SuperIDR in an
undergraduate Ichthyology class as an aid to fish species identification
and found that the use of SuperIDR yielded a higher likelihood of success
in species identification than using traditional methods, including
the dichotomous key, fish web sites, notes, etc.