Authors:
Himanshu Agrahari
1
;
Yuji Iwahori
2
;
M. K. Bhuyan
1
;
Somnath Ghorai
1
;
Himanshu Kohli
1
;
Robert J. Woodham
3
and
Kunio Kasugai
4
Affiliations:
1
Indian Institute of Guwahati, India
;
2
Chubu University, Japan
;
3
University of British Columbia, Canada
;
4
Aichi Medical University, Japan
Keyword(s):
Endoscopy, Discrete Singular Convolution, Histogram of Oriented Gradients (HOG), Conic Fitting, Support Vector Machine.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image Understanding
;
Medical Imaging
;
Object Recognition
;
Pattern Recognition
;
Software Engineering
Abstract:
Endoscopy is a very powerful technology to examine the intestinal tract and to detect the presence of any possible abnormalities like polyps, the main cause of cancer. This paper presents an edge based method for polyp detection in endoscopic video images. It utilizes discrete singular convolution (DSC) algorithm for edge detection/segmentation scheme, then by using conic fitting techniques (ellipse and hyperbola) potential candidates are determined. These candidates are first rotated so as to make major axis in the x-axis direction, and
then classified as polyp or non-polyp by SVM classifier which is trained separately for ellipse and hyperbola with HOG features.