Comparison of k-NN, SVM, and NN in Pit Pattern Classification of Zoom-Endoscopic Colon Images using Co-Occurrence Histograms

Author

Häfner, M. ; Gangl, A. ; Wrba, F. ; Thonhauser, K. ; Schmidt, H.-P. ; Kastinger, Ch ; Uhl, A. ; Vécsei, A.

Author_Institution

Vienna Med. Univ., Vienna

fYear

2007

fDate

27-29 Sept. 2007

Firstpage

516

Lastpage

521

Abstract

Co-occurrence histograms are used as features to classify magnifying endoscope imagery with k-NN, SVM, and NN classifiers. In the k-NN classification case these histograms may improve the classification accuracy of simple ID color histograms up to 10% in the 2 classes case and up to 5% in the 6 classes case. The classification results of SVM and NN classifiers have turned out to be noncompetitive and do not improve the classification result of ID color histograms.

Keywords

biological organs; endoscopes; image classification; image colour analysis; medical image processing; support vector machines; 1D color histograms; NN classifiers; SVM; colon images; k-NN classification; magnifying endoscope imagery; pit pattern classification; support vector machine; Cancer; Colon; Colonoscopy; Endoscopes; Histograms; Lesions; Neural networks; Pattern classification; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing and Analysis, 2007. ISPA 2007. 5th International Symposium on

Conference_Location

Istanbul

ISSN

1845-5921

Print_ISBN

978-953-184-116-0

Type

conf

DOI

10.1109/ISPA.2007.4383747

Filename

4383747