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

Contour or boundary descriptors may be used in content-based image retrieval to effectively identify appropriate images when image content consists primarily of a single object of interest. The registration of object contours for the purposes of comparison is complicated when the objects of interest are characterized by open contours and when reliable feature points for contour alignment are absent. We present an application that employs an iterative approach to the alignment of open contours for the purposes of image retrieval and demonstrate its success in identifying individual bottlenose dolphins from the profiles of their dorsal fins.

[1]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Taein Lee,et al.  Active contour models , 2005 .

[3]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Josef Kittler,et al.  Minimum error thresholding , 1986, Pattern Recognit..

[5]  N. Kehtarnavaz,et al.  A String Matching Computer-Assisted System for Dolphin Photoidentification , 2004, Annals of Biomedical Engineering.

[6]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[7]  Helias A. Udo de Haes,et al.  IDENTIFICATION OF INDIVIDUAL SPERM WHALES BY WAVELET TRANSFORM OF THE TRAILING EDGE OF THE FLUKES , 1998 .

[8]  Babak Nadjar Araabi,et al.  Assisting Manual Dolphin Identification by Computer Extraction of Dorsal Ratio , 1999, Annals of Biomedical Engineering.

[9]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.