Date of Award
5-2006
Degree Type
Thesis
Degree Name
M.S.
Degree Program
Computer Science
Department
Computer Science
Major Professor
Fu, Bin
Second Advisor
Deng, Jing
Third Advisor
Chen, Yixin
Abstract
It is estimated that less than ten percent of the world's species have been discovered and described. The main reason for the slow pace of new species description is that the science of taxonomy, as traditionally practiced, can be very laborious: taxonomists have to manually gather and analyze data from large numbers of specimens and identify the smallest subset of external body characters that uniquely diagnoses the new species as distinct from all its known relatives. The pace of data gathering and analysis can be greatly increased by the information technology. In this paper, we propose a content-based image retrieval system for taxonomic research. The system can identify representative body shape characters of known species based on digitized landmarks and provide statistical clues for assisting taxonomists to identify new species or subspecies. The experiments on a taxonomic problem involving species of suckers in the genera Carpiodes demonstrate promising results.
Recommended Citation
Teng, Fei, "A Content-Based Image Retrieval System for Fish Taxonomy" (2006). University of New Orleans Theses and Dissertations. 377.
https://scholarworks.uno.edu/td/377
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.