DocumentCode
2672974
Title
Expert computer vision based crab recognition system
Author
Han, Ki Jin ; Tewfik, Ahmed H.
Author_Institution
Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA
Volume
1
fYear
1996
fDate
16-19 Sep 1996
Firstpage
649
Abstract
Two species of crabs are Chionoecetes bairdi and C. opilio and their hybrids live in the Bering Sea. The two species differ in generic, morphological and morphometric characteristics. Inter breeding of C. bairdi and C. opilio results in a hybrid form with intermediate morphological and morphometric characteristics. These species were determined by analyzing the empirical covariance matrices associated with the two species and the hybrid and by taking into account the statistical reliability of the estimated principal components. A modified eigen image classifier is implemented based on the assumption that the data is drawn from multivariate Gaussian distributions with different means and covariance matrices. The clustering technique is introduced to minimize the misclassification rate of the eigen image classifier
Keywords
Gaussian distribution; aquaculture; biology computing; computer vision; covariance matrices; eigenvalues and eigenfunctions; expert systems; image classification; statistical analysis; Bering Sea; Chionoecetes bairdi; Chionoecetes opilio; clustering technique; covariance matrices; crab recognition system; empirical covariance matrices; estimated principal components; expert computer vision; generic characteristics; hybrid form; interbreeding; intermediate morphological characteristics; intermediate morphometric characteristics; means; misclassification rate; modified eigenimage classifier; morphological characteristics; morphometric characteristics; multivariate Gaussian distributions; statistical reliability; Computer vision; Covariance matrix; Filtering; Gaussian distribution; Genetics; Image analysis; Image edge detection; Low pass filters; Nonlinear filters; Protection;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1996. Proceedings., International Conference on
Conference_Location
Lausanne
Print_ISBN
0-7803-3259-8
Type
conf
DOI
10.1109/ICIP.1996.560961
Filename
560961
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