Evaluation of Feature Descriptor on D-Saddle Keypoint Detection in Retinal Image Registration

被引：0

作者：

Chan, Nurshafira Hazim ^{[1
]}

Hasikin, Khairunnisa ^{[1
]}

Kadri, Nahrizul Adib ^{[1
]}

机构：

[1] Univ Malaya, Fac Engn, Dept Biomed Engn, Kuala Lumpur, Malaysia

来源：

2019 IEEE 15TH INTERNATIONAL COLLOQUIUM ON SIGNAL PROCESSING & ITS APPLICATIONS (CSPA 2019) | 2019年

关键词：

retina; registration; detector; descriptor; feature-based; FUNDUS IMAGES; ROBUST; ALGORITHM;

D O I：

10.1109/cspa.2019.8696015

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper presents an investigation of the common feature descriptor on D-Saddle keypoint detection to guide the retinal image registration process. Few feature descriptor methods have been chosen which are Histogram of Oriented Gradient (HOG), Speeded-Up Robust Features (SURF), Binary Robust Invariant Scalable Keypoints (BRISK) and Fast Retina Keypoints (FREAK). Findings indicate that the combination of SURF descriptor with D-Saddle detection produced more significant inliers as compared to the other state-of-the-art combinations of descriptors and keypoint detections.

引用

页码：178 / 181

页数：4

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