A fractional-order edge detection operator for medical image structure feature extraction

This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency...

Full description

Saved in:
Bibliographic Details
Main Authors: Dan Tian, Jingfei Wu, Yajie Yang
Format: Conference Proceeding
Language:English
Subjects:
Feature extraction
Fractional-order
Image edge detection
Medical diagnostic imaging
Medical Image
Noise
Sobel Detection
Thresholding Selection
Ultrasonic imaging
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper introduces a novel fractional-order gradient operator for medical image structure feature extraction. The proposed operator can be seen as generalization of the first-order Sobel operator based on the GL fractional derivative definition. The generalization goal is to utilize the frequency characteristic of the fractional derivative for extracting more structure feature details. A thresholding is set based on the average fractional-order gradient for marking the edge points, and then the image structure can be extracted. Experiments show that the proposed fractional-order operator yields good visual effects.
ISSN:1948-9439
1948-9447
DOI:10.1109/CCDC.2014.6853103